journal of infectious diseases & travel medicine

Travel restrictions and infectious disease outbreaks

Affiliations.

• 1 Ada Health GmbH, Berlin, Germany.
• 2 London School of Economics and Political Science, London, UK.
• 3 London School of Hygiene & Tropical Medicine, London, UK.
• 4 Global Health Centre, Graduate Institute of International and Development Studies, Geneva, Switzerland.
• 5 Centre on Global Health Security, Chatham House, London, UK.
• PMID: 32297935
• PMCID: PMC7188139
• DOI: 10.1093/jtm/taaa050

Background: A key purpose of the International Health Regulations (IHR) is to prevent unwarranted interruptions to trade and travel during large and/or transnational infectious disease outbreaks. Nevertheless, such outbreaks continue to disrupt the travel industry. This aspect of the IHR has received little attention in the academic literature despite its considerable impact on affected States and commercial activity. This article outlines the challenges and gaps in knowledge regarding the relationship between outbreaks and the travel sector and discusses the opportunities for further research and policy work to overcome these challenges.

Methodology: We conducted a literature review on the relationship between outbreaks and travel restrictions, with a particular focus on the 2014-16 Ebola epidemic in West Africa. This review was complemented by an expert roundtable at Chatham House and further supported by case studies and qualitative interviews.

Results: Numerous travel stakeholders are affected by, and affect, large-scale infectious disease outbreaks. These stakeholders react in different ways: peer pressure plays an important role for both governments and the travel sector, and the reactions of the media and public influence and are influenced by these stakeholders. While various data sources on travel are available, and World Health Organization is mandated to work with States, there is no recognized coordinating body to disseminate timely, consistent, reliable and authoritative information and best practices to all stakeholders.

Conclusion: This article highlights the interdependent relationship between various travel stakeholders. The reasons for interruption of travel during the 2014-16 Ebola outbreak were complex, with decisions by States only partly contributing to the cessation. Decisions by non-state actors, particularly the travel industry itself, contributed significantly and were based on a variety of factors. Further research, analysis and policy development are required to mitigate the health and economic consequences of infectious disease outbreaks. Any further research will also need to take account of COVID-19 travel-related issues.

Keywords: Infectious disease outbreaks; Travel restrictions.

© International Society of Travel Medicine 2020. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: [email protected].

Publication types

• Historical Article
• Research Support, Non-U.S. Gov't
• Africa, Western
• Betacoronavirus
• Communicable Disease Control / methods*
• Communication
• Coronavirus Infections
• Decision Making
• Disease Outbreaks / prevention & control*
• Hemorrhagic Fever, Ebola / epidemiology*
• Hemorrhagic Fever, Ebola / history
• History, 21st Century
• Pneumonia, Viral

Travel Medicine and Tourist Health

• First Online: 30 November 2021

Cite this chapter

• Peter A. Leggat   ORCID: orcid.org/0000-0002-8749-014X 5  

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Following a period of steady growth in tourism, COVID-19 has caused a tremendous decrease in tourist numbers travelling around the world. With the advent of COVID-19 vaccine programs we will no doubt see a resurgence in travel, but it may take years to recover to pre-COVID-19 levels. Travel medicine aims to assist travellers remain healthy and safe during their travels and will be very important to the recovery of tourism globally. Indeed, travel medicine will likely play a key role in when we can travel normally again.

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Leggat, P.A. (2021). Travel Medicine and Tourist Health. In: Wilks, J., Pendergast, D., Leggat, P.A., Morgan, D. (eds) Tourist Health, Safety and Wellbeing in the New Normal. Springer, Singapore. https://doi.org/10.1007/978-981-16-5415-2_2

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• v.18(2); 2017 Apr

Travel medicine: Part 1–The basics

Kazuhiro kamata.

1 Department of Medicine, JCHO Tokyo Joto Hospital, Kotoku, Tokyo, Japan

Richard B Birrer

2 Department of Emergency Medicine, Cornell University School of Medicine, New York, NY, USA

Yasuharu Tokuda

3 Japan Community Healthcare Association (JCHO), Tokyo, Japan

International travels for tourism and business purposes continue to increase annually, while the global terrorism and the risk of lethal viral infections are currently real concerns. It is important that primary care physicians assess travel risk and adequately prepare the prospective traveler for trips. Appropriate vaccines should be administered and an emergency self‐kit recommended. Patient should be educated about safe travel habits and a posttravel follow‐up process established. Further, traveling healthcare professionals may be called upon to assist an ill patient at any time during their journey. In these 2‐part special articles, we provide a practical brief summary of up‐to‐date travel medicine basics for primary care physicians.

1. Travelers’ Trend

The number of international travelers annually is continuously growing, although there was a dip in travelers, following the World Trade Center Terrorism Attack at New York City on 9/11/2001. Most international travelers go to developed countries, particularly Europe, but a substantial number of expatriates and adventure travelers go to developing countries around the world. It is expected that both trends will continue to increase over the next decade. Primary care physician is likely to be consulted by prospective travelers with respect to required vaccines, health hazards in host countries and adequate preparation to avoid illness. 1 , 2

2. Preparations

All prospective travelers should have their health history reviewed for the possible health risks of the planned itinerary. Information such as the dates, duration, routes, style of travel (eg, budget vs luxury), accommodations, and activities (eg, business vs leisure) should be collected. 3

It is important to let the prospective traveler understand that he/she has a 15% chance of becoming sick during their trip in average, 4 but the chance of a serious illness or death is very small (Table  1 ). A study about the incidence of health problems during a stay in developing countries 2008 indicates that travelers’ diarrhea has the greatest incidence (20%‐60% of all travelers). 5

Estimated disease frequency of 100 000 travelers to a developing country for 1 mo

Additional risks include accidental injury, environmental hazards (eg, hypo‐or hyperthermia), crime and assault, underlying medical and psychiatric problems, animal bites, stings and envenomations, and altitude‐related illness. 6 The greatest cause for mortality among travelers is cardiovascular disease. The highest external cause for mortality among travelers is motor vehicle accident, followed by drowning.

On the other hand, infectious disease causes only 1% death among travelers. 6 Despite the low mortality, the incidence of infectious disease is very high among travelers, and common infectious diseases with risks to international travelers are listed in Table  2 . Enterotoxigenic E. coli (ETEC) is the leading pathogen in travelers’ diarrhea. 5 Common health problems among travelers include circadian desynchronosis (jet lag), sunburn, dehydration, and water‐related problems (eg, exposure to infectious agents, near‐drowning, boating, and diving accidents).

Common infectious diseases with risks to international travelers

A focused past medical history and review of systems should be performed, emphasizing age specific issues, underlying illness, and immunosuppression (eg, splenectomy, certain medications), allergies, and vaccinations. 7 Individuals with inflammatory bowel disease do not have increased bouts of traveler's diarrhea compared to normal travelers, but when it occurs it is often severe. Travelers with congestive heart failure or chronic obstructive pulmonary disease may decompensate at altitude including a long haul flight. During pregnancy, or its possibility, risk‐taking behaviors (eg, off‐road trekking and adventure.) should be avoided. 8

The physical examination should be updated particularly whether the patient has a chronic illness such as diabetes or cardiovascular pathology. Medications should be reviewed and adequate prescriptions provided for a secondary travel supply. Ideally, a summary of the patient's health data should accompany her/him in case the patient becomes ill while traveling. Not only the destination but also mode of travel should be considered. Open jaw stopovers may expose the unwary traveler to an infectious or traumatic event since the patient may have to get commercial sexual contacts or ride a reckless vehicle unexpectedly in cities the patient does not prospectively collect information on.

3. Patient Education

Sufficient time should be allowed for tailored patient education. The session should summarize the visit with a clear discussion of traveler's fitness for travel, important precautions, health insurance coverage for hospitalization, and evacuation, the availability of healthcare in the planned destination and the importance of a follow‐up visit, particularly for long‐term stays, such as expatriates working in developing countries or adventure travelers upon return to home.

Personal hygiene, especially hand washing, should be stressed. Food and water precautions include the use of bottled water, eating food that is cooked hot, and cold food when it is cold. All fresh fruit should be eaten after peeling. Unpasteurized dairy products should be avoided unless it was prepared from bottled water.

Vector precautions include covering exposed skin (ie, blousing) using insect repellent containing DEET (N, N‐diethyl‐meta‐toluamide) 25%‐50%, treating outer clothing with permethrin, using permethrin‐impregnated bed netting, insect screens over open windows, when possible staying in air‐conditioned rooms, using aerosol insecticide indoors and pyrethroid coils outdoors and inspecting for ticks. Exposure to sexually transmitted diseases, hepatitis B and C and HIV can occur with unprotected sexual activity, tattooing and body piercing, the administration of blood products, and dental and surgical procedures. 9 Visitors (eg, veterinarians) to countries with elevated rabies risk should receive the vaccine and those who are bitten or scratched should be advised to immediately seek medical help and postexposure immunization and immunoglobulin. 10

Travelers should be clearly warned that unsafe pedestrian activities in developing countries carry a high risk of injury. Night travel should be avoided and when traveling by motorized vehicle seat belts should be used (car seat with infants and small children). Alcohol should be used with discretion and only in a controlled environment. It accelerates dehydration on an airplane. Lastly, a clear understanding of local crime risks is essential. 11 This should include scam awareness, situational awareness, and location avoidance. 12

4. Preventive Care

Table  3 lists the vaccines commonly indicated for a traveler. 13 , 14 , 15 Ideally, there should be sufficient time to provide the necessary vaccines so that their efficacy is maximized. Individuals with liver disease such as cirrhosis should receive all hepatitis vaccinations. 9 Special consideration should be given for rabies vaccine if the traveler is planning to a prolonged visit or work in an indigenous area. 10 Live virus vaccines (eg, measles, mumps, rubella, and varicella) are generally contraindicated in the pregnant female, or one who may conceive while traveling. 16

Vaccines commonly indicated for a traveler

However, risk and benefit need to be examined in some individual cases. Contraception for 2 months after the vaccination of live viruses should be advised. Yellow fever vaccination may be considered after the 6th month of pregnancy, when the risk of exposure is deemed greater than the risk to the fetus. Pregnant women should be advised not to travel to areas where there is a risk of exposure to yellow fever. 17

Chemoprophylaxis and self‐care medications are listed in Table  4 . These include medications for malaria, diarrheal illnesses, high altitude, and motion sickness. 18 , 19 , 20 , 21 , 22 , 23 The patient should be instructed on the appropriate use of these medications and when to seek help should illness occur. Mefloquine has been known to exacerbate depression. 24 , 25 Scopolamine can lead to dysuria or urinary obstruction in male travelers with benign prostatic hypertrophy. 26

Travel Medications: Prophylaxis and Self‐Care

A travel emergency kit can also be discussed with the patients. Content suggestions include a copy of medical records and extra pair of glasses, prescription medications, over‐the counter medicines and supplies (eg, analgesics, decongestant, cold medicine, cough suppressant, antibiotic/antifungal/hydrocortisone creams, antacids), gauze bandages, tape, self‐adhering elastic bandages, moleskin, insect repellant, sunscreen, lip balm, tweezers, scissors, and a thermometer. 27

5. Healthcare Information Resources

There are a number of reliable sources available for healthcare professionals and travelers. 28 A number of them provide regular updates, travel notices and warnings based on infectious outbreaks, environmental dangers, or political unrest. A recommended list is provided in Table  5 . A number of textbooks and journals are also available if more detailed information is required (Table  6 ).

Recommended list of healthcare information resources in travel medicine

Major journals and textbooks for travel medicine

Conflict of Interest

The authors have stated explicitly that there are no conflicts of interest in connection with this article.

Kamata K, Birrer RB, Tokuda Y. Travel medicine: Part 1–The basics . J Gen Fam Med . 2017; 18 :52–55. https://doi.org/10.1002/jgf2.39 [ PMC free article ] [ PubMed ] [ Google Scholar ]

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Tropical Diseases, Travel Medicine and Vaccines

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Methaemoglobin as a surrogate marker of primaquine antihypnozoite activity in Plasmodium vivax malaria: a systematic review and individual patient data meta-analysis

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Background The 8-aminoquinolines, primaquine and tafenoquine, are the only available drugs for the radical cure of Plasmodium vivax hypnozoites. Prior evidence suggests that there is dose-dependent 8-aminoquinoline induced methaemoglobinaemia and that higher methaemoglobin concentrations are associated with a lower risk of P. vivax recurrence. We undertook a systematic review and individual patient data meta-analysis to examine the utility of methaemoglobin as a surrogate endpoint for 8-aminoquinoline antihypnozoite activity to prevent P. vivax recurrence.

Methods We conducted a systematic search of Medline, Embase, Web of Science, and the Cochrane Library, from 1 January 2000 to 29 September 2022 inclusive, of prospective clinical efficacy studies of acute, uncomplicated P. vivax malaria mono-infections treated with radical curative doses of primaquine. The day 7 methaemoglobin concentration was the primary surrogate outcome of interest. The primary clinical outcome was the time to first P. vivax recurrence between day 7 and day 120 after enrolment. We used multivariable Cox proportional-hazards regression with site random-effects to characterise the time to first recurrence as a function of the day 7 methaemoglobin percentage (log 2 transformed), adjusted for the partner schizontocidal drug, the primaquine regimen duration as a proxy for the total primaquine dose (mg/kg), the daily primaquine dose (mg/kg), and other factors. The systematic review protocol was registered with PROSPERO (CRD42023345956).

Findings We identified 219 P. vivax efficacy studies, of which eight provided relevant individual-level data from patients treated with primaquine; all were randomised, parallel arm clinical trials assessed as having low or moderate risk of bias. In the primary analysis dataset, there were 1747 G6PD-normal patients enrolled from 24 study sites across 8 different countries (Indonesia, Brazil, Vietnam, Thailand, Peru, Colombia, Ethiopia, India). We observed an increasing dose-response relationship between the daily weight-adjusted primaquine dose and day 7 methaemoglobin level. For a given primaquine dose regimen, an observed doubling in day 7 methaemoglobin percentage was associated with an estimated 30% reduction in the risk of vivax recurrence (adjusted hazard ratio = 0.70; 95% CI = [0.57, 0.86]; p = 0.0005). These pooled estimates were largely consistent across the study sites. Using day 7 methaemoglobin as a surrogate endpoint for recurrence would reduce required sample sizes by approximately 40%.

Conclusions For a given primaquine regimen, higher methaemoglobin on day 7 was associated with a reduced risk of P. vivax recurrence. Under our proposed causal model, this justifies the use of methaemoglobin as a surrogate endpoint for primaquine antihypnozoite activity in G6PD normal patients with P. vivax malaria.

Competing Interest Statement

I have read the journal's policy and the authors of this manuscript have the following competing interests: JAG and GCKWK are former employees of GSK and hold shares in GSK and AstraZeneca. GCKWK reports travel support from AstraZeneca. JKB and KT receive institutional research funding from Medicines for Malaria Venture. JKB reports GSK, Wellcome Trust, and Sanaria participation on the US National Institutes of Health data safety monitoring board and membership of the editorial board of Travel Medicine and Infectious Disease and the guidelines development group for malaria control and elimination, Global Malaria Programme, WHO. RJC, JKB, and RNP report contributions to Up-to-Date. All other authors declare no competing interests.

Clinical Protocols

https://www.iddo.org/document/primaquine-methaemoglobin-study-group-statistical-analysis-plan-0

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Author declarations.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

All studies included in our meta-analysis provided pseudonymised individual data and had obtained ethical approvals from the corresponding site of origin. Therefore, additional ethical approval was not required for the current analysis, as per the Oxford Tropical Research Ethics Committee.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Data Availability

Pseudonymised participant data used in this study can be accessed via the WorldWide Antimalarial Resistance Network ( wwarn.org ). Requests for access will be reviewed by a data access committee to ensure that use of data protects the interests of the participants and researchers according to the terms of ethics approval and principles of equitable data sharing. Requests can be submitted by email to malariaDAC{at}iddo.org via the data access form available at https://www.wwarn.org/working-together/sharing-accessing-data/accessing-data . WWARN is registered with the Registry of Research Data Repositories ( https://www.re3data.org/ ).

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Open Access

Peer-reviewed

Research Article

An evaluation of the impact of social and structural determinants of health on forgone care during the COVID-19 pandemic in Baltimore, Maryland

Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Center for Infectious Disease and Nursing Innovation, Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America, Center for Health Security, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, United States of America

Roles Investigation, Writing – review & editing

Affiliation Center for Infectious Disease and Nursing Innovation, Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America

Roles Conceptualization, Methodology, Writing – review & editing

Affiliation Johns Hopkins University, School of Nursing, Baltimore, MD, United States of America

Affiliation FHI 360, Durham, NC, United States of America

Roles Methodology, Writing – review & editing

Affiliation Department of Epidemiology, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, United States of America

Affiliation Center for Health Security, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, United States of America

Affiliation Department of Pediatrics, Johns Hopkins University, School of Medicine, Baltimore, MD, United States of America

• Diane Meyer, 
• Kelly Lowensen, 
• Nancy Perrin, 
• Ayana Moore, 
• Shruti H. Mehta, 
• Cheryl R. Himmelfarb, 
• Thomas V. Inglesby, 
• Jacky M. Jennings, 
• Alexandra K. Mueller, 

• Published: May 13, 2024
• https://doi.org/10.1371/journal.pone.0302064
• Peer Review
• Reader Comments

Evidence suggests that reductions in healthcare utilization, including forgone care, during the COVID-19 pandemic may be contributing towards excess morbidity and mortality. The objective of this study was to describe individual and community-level correlates of forgone care during the COVID-19 pandemic. We conducted a cross-sectional, secondary data analysis of participants (n = 2,003) who reported needing healthcare in two population-representative surveys conducted in Baltimore, MD in 2021 and 2021–2022. Abstracted data included the experience of forgone care, socio-demographic data, comorbidities, financial strain, and community of residence. Participant’s community of residence were linked with data acquired from the Baltimore Neighborhood Indicators Alliance relevant to healthcare access and utilization, including walkability and internet access, among others. The data were analyzed using weighted random effects logistic regression. Individual-level factors found to be associated with increased odds for forgone care included individuals age 35–49 (compared to 18–34), female sex, experiencing housing insecurity during the pandemic, and the presence of functional limitations and mental illness. Black/African American individuals were found to have reduced odds of forgone care, compared to any other race. No community-level factors were significant in the multilevel analyses. Moving forward, it will be critical that health systems identify ways to address any barriers to care that populations might be experiencing, such as the use of mobile health services or telemedicine platforms. Additionally, public health emergency preparedness planning efforts must account for the unique needs of communities during future crises, to ensure that their health needs can continue to be met. Finally, additional research is needed to better understand how healthcare access and utilization practices have changed during versus before the pandemic.

Citation: Meyer D, Lowensen K, Perrin N, Moore A, Mehta SH, Himmelfarb CR, et al. (2024) An evaluation of the impact of social and structural determinants of health on forgone care during the COVID-19 pandemic in Baltimore, Maryland. PLoS ONE 19(5): e0302064. https://doi.org/10.1371/journal.pone.0302064

Editor: Tae-Young Pak, Sungkyunkwan University School of Social Sciences, REPUBLIC OF KOREA

Received: August 24, 2023; Accepted: March 27, 2024; Published: May 13, 2024

Copyright: © 2024 Meyer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: Research reported in this publication was supported by the National Institute of Nursing Research (award number 1F31NR080834-01) and the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award numbers P30AI094189-09S1 and UM1AI068619. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: S. Mehta receives material support from Abbott Diagnostics. This does not alter our adherence to PLOS ONE policies on sharing data and materials. The authors do not have any other conflicts of interest to disclose

Introduction

Evidence suggests that reductions in healthcare utilization during the Coronavirus disease 2019 (COVID-19) pandemic may be contributing towards excess morbidity and mortality [ 1 – 3 ]. Much of this evidence consists of studies describing changes in the volume of services rendered, such as trends in hospital admissions and emergency department usage [ 1 , 4 , 5 ]. Fewer studies have evaluated COVID-19 related changes in healthcare utilization through the lens of patient-reported forgone care, which is defined as healthcare that is perceived as needed by the person but not received, and includes delayed, missed, or skipped visits with a healthcare provider [ 6 , 7 ].

Existing studies have identified several individual-level social and structural determinants of health (SSDoH) as important correlates of forgone care during the pandemic, although the findings have been at times contradictory, likely related to the heterogeneity of sampling [ 8 – 19 ]. Czeisler et al., using a nationally representative sample of US adults, found the prevalence ratio of forgone care in non-Hispanic Black adults to be 1.6 times that of non-Hispanic White adults in June 2020 [ 10 ]. However, another nationally-representative survey of forgone care from March to July 2020 among adults did not identify any statistically significant difference in the frequency of forgone care by race/ethnicity [ 9 ]. A separate study that evaluated forgone care among Medicare beneficiaries found a higher prevalence among non-Hispanic White beneficiaries (22.5%), compared to non-Hispanic Black beneficiaries (12.6%) in the summer of 2020, although these differences dissipated when looking at forgone care in the fall of 2020 and winter of 2021 [ 16 ]. Other factors identified as being significantly correlated with forgone care, although at times with mixed results, include experiencing food or income insecurity; education level; having comorbid conditions, including mental health conditions and functional disabilities; both older and younger age; having health insurance; identifying as a member of the LGBTQ+ community; and experiencing racial discrimination [ 8 – 13 , 15 – 17 , 19 ]. These studies may indicate that certain individuals and communities experienced disproportionate impacts on healthcare access and utilization during the pandemic, leading to forgone care.

Community-specific SSDoH, such as Area Deprivation Index, internet coverage, walkability, and ethnic segregation are related to health outcomes [ 20 – 26 ]. Studies have identified geographic inequities related to the COVID-19 pandemic, including COVID-19 case counts and mortality rates [ 27 , 28 ] and inequitable access to testing and treatment [ 29 – 31 ], but few have acknowledged these factors and their associations with forgone care. Similar geographic inequities may have occurred in who experienced forgone care, such as in communities with high rates of poverty, those with ethnic segregation, and those without resources such as internet coverage. For example, several community-level factors have been cited in the literature as reasons for forgoing care during the pandemic, including closures of local health facilities, transportation challenges, and lack of resources required for telemedicine [ 1 , 9 , 32 , 33 ]. Also concerning is that many of the communities that suffered higher rates of SARS-CoV-2 infection also likely needed additional healthcare services as a result.

Forgone care can have drastic consequences on individual and community health. Delayed and cancelled preventive care, including immunizations, dental cleanings, and cancer screenings, will have long-term health implications that go well beyond the end of the COVID-19 pandemic. For example, one study identified decreases in screenings for breast, lung, colon, cervical, and prostate cancer ranging from 60% to 82% at one large health center in Massachusetts [ 34 ]. Delayed treatment for emergent conditions such as strokes, heart attacks, and orthopedic trauma likely have led to worse prognoses and more severe outcomes [ 35 – 37 ]. Furthermore, studies conducted prior to the pandemic found that those with chronic conditions are more likely to forgo care [ 12 ]. Given that the pandemic introduced or exacerbated existing barriers to healthcare access, these individuals could be at higher risk for severe downstream consequences of interruptions in care. This is reflected in mortality data published by the US Centers for Disease Control and Prevention, which suggests a large increase in excess deaths from chronic conditions such as heart disease and diabetes, highlighting the importance of continued access to care and the potential consequences of forgone care [ 38 ].

The aim of this study was to evaluate the impact of individual and community-level SSDoH on healthcare utilization during the COVID-19 pandemic by specifically looking at forgone care among a sample of adults living in Baltimore, Maryland. The objective was to determine whether community-level correlates accounted for forgone care above and beyond any individual participant-level correlates. Understanding the intersections of forgone care during the COVID-19 pandemic with SSDoH is critical to providing a comprehensive view of the health impacts of the pandemic and to identifying which individuals and communities experienced the greatest interruptions in care.

Study design and data sources

This was a secondary data analysis using baseline data abstracted from two parent studies funded by the National Institute of Allergy and Infectious Diseases. The combined analytic sample leveraged the strengths of two robust sampling strategies used in the parent studies, increasing the overall sample size, and helping to ensure adequate representation of economically disadvantaged and historically excluded communities that may not be included in the current COVID-19 forgone care literature.

This nested study used a cross-sectional design to examine individual and community-level factors associated with forgone care during the COVID-19 pandemic in Baltimore, MD. Data abstracted from the parent studies included responses to survey questions regarding demographics, comorbidities, healthcare needs, and forgone care during the COVID-19 pandemic. For the purposes of this study, forgone care was defined as healthcare that was skipped, missed, or delayed during the COVID-19 pandemic. The two parent studies are described in more detail below.

The Community Collaborative to Combat COVID-19 study.

The Community Collaborative to Combat COVID-19 (C-Forward) parent study was a two-phased comparative effectiveness trial. Enrollment of participants occurred from February 2021 to December 2022. The study aimed to evaluate three different SARS-CoV-2 testing modalities (fixed site, mobile, and home-based) using a representative sample of Baltimore households. The study enrolled households (HH) using a multi-staged sampling approach, organized by census block groups that were stratified by socioeconomic status and race/ethnicity, with oversampling of historically excluded and under-resourced populations (e.g., Hispanic/LatinX populations, low-income whites).

Household recruitment was multi-modal and included doorhangers, mailings, telephone calls, and online methods. The study included enrollment of one eligible member per HH, 18 years of age or older, who was able to provide informed consent (designated as the “HH index member”). The HH index member completed a baseline survey that covered demographics; history of COVID-19 symptoms, testing and treatment; adoption of preventive behaviors; comorbidities and health care access and utilization (including forgone care); COVID-19 impact and pandemic stress; mental health and substance abuse; and knowledge and attitude towards COVID-19. This survey was completed electronically, by mail, or via telephone with a trained research assistant and entered into REDCap. HH index members also received SARS-CoV-2 antigen and antibody testing and other serum testing (e.g., chemistry profiles). A total of n = 1,978 HH index members were enrolled. Additional information about this study, including other study phases that were not included in this secondary data analysis, can be found on clinicaltrials.gov (clinical trial identifier # NCT04673292).

The COVID-19 Prevention Network 5002 study.

The COVID-19 Prevention Network 5002 (CoVPN 5002) parent study was a multi-site, cross-sectional SARS-CoV-2 prevalence study conducted from March to July 2021. The study used a venue-time sampling strategy, with random selection of venues and enrollment times. Venues included low-income housing, transitional housing, shelters, soup kitchens, places of worship, local federally qualified health centers, and rehabilitation centers, among others [ 39 ].

All individuals accessing the selected venue during the randomly selected time/location slot were approached to assess interest and eligibility to enroll in the study. Adults and children greater than 2 months of age who were willing and able to provide consent (assent for those <18 years of age, with the consent of a guardian) were eligible. Participants completed a paper-based survey with a research assistant that included questions on demographics; medical history (including forgone care); COVID-19 history included exposure; knowledge, attitudes, and behavior about COVID-19; economic impacts of COVID-19; and willingness to take the COVID-19 vaccine. All survey responses were later entered into Medidata. Individuals also received SARS-CoV-2 antigen and antibody testing. A total of n = 1,022 individuals enrolled in the study at the Baltimore, Maryland site. Additional information about this study can be found on clinicaltrials.gov (clinical trial identifier # NCT04658121). The secondary data analysis presented in this manuscript describes only data collected from the Baltimore research site.

Secondary data analysis

Inclusion and exclusion criteria..

All parent study participants who reported needing any care type during the COVID-19 pandemic in the parent study survey, including chronic, preventive, or emergent care or a major medical or dental procedure were included ( Fig 1 ); all other parent study participants were dropped (n = 888). Parent study questions can be located in Supplement 1. Participants under the age of 18 were also dropped regardless of whether or not they needed any type of care (n = 22), as C-Forward only included enrollment of HH index members who were ≥ 18 years of age.

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https://doi.org/10.1371/journal.pone.0302064.g001

Individuals were also excluded if it could not be ascertained as to whether they needed any type of care during the pandemic (e.g., they left these survey questions blank or responses were discordant; n = 44) or it was unclear whether they had experienced the outcome of forgone care (n = 42). Surveys that had seven or more incomplete demographic questions were also dropped (n = 1).

Outcome variable.

The outcome variable for this study was participant-reported forgone care on enrollment in either of the parent studies. This included any forgone care experienced since the beginning of the COVID-19 pandemic, measured from March 1, 2020 until completion of the survey. Questions on forgone care assessed the need for and receipt of chronic or preventive care, emergent care, and major medical or dental procedures. All C-Forward participants responded to questions on needing/forgoing chronic, preventive, and emergent care and elective/dental procedures. For the CoVPN 5002 study, a supplemental survey on needing/forgoing emergent care and elective/dental procedures was added in April 2021 to the Baltimore, MD research site only. Prior to that date, participants only responded to survey questions on needing/forgoing chronic/preventive care.

Independent variables—Individual level.

The selection of individual-level variables was informed by the Gelberg Behavioral Model for Vulnerable Populations [ 40 ]. This framework, a revision of the Andersen and Newman Model of Healthcare Utilization [ 41 ], was chosen as it includes determinants of healthcare system access and utilization relevant to underserved populations living in Baltimore, which has higher rates of poverty, homelessness, crime, and drug use in comparison to other cities of its size as well as widespread disparities across the SSDoH [ 42 – 45 ]. Our adapted model included individual and community-level factors related to healthcare utilization and organizes them into three categories: predisposing—factors that may increase the propensity to seek care; enabling/impeding—factors that may enable or impede use of the health system; and need—factors that reflect perceived need for care [ 40 , 41 ]. For this study, predisposing factors included age, sex at birth, race, marital status, employment status, disability status, and education level. Enabling/impeding factors included income, loss of housing during the pandemic, and worrying about paying rent/mortgage during the pandemic. Need factors included number of comorbidities, presence of functional limitations, mental illness, and alcohol/substance and injection drug use. Each of these variables were measured using survey data from the two parent studies (see supplement 1 for parent surveys). Responses were consolidated across the two surveys by sociodemographic topic (e.g., sex, age) and sub-categories (e.g., female, male) were created to be inclusive of the wording of the parent studies.

Independent variables—Community level.

Participants were assigned community-level factors based on their community statistical area (CSA) of residence. CSA’s are clusters of neighborhoods that were developed by Baltimore City’s Planning Department and are based on city neighborhoods [ 46 ]. There are 55 CSA’s in the city of Baltimore, with boundaries that align directly to census tracts (46). The population of a given CSA ranges from 5,000 to 20,000 people and consist of anywhere from 1–8 Census Tracts [ 47 ]. C-Forward participants were matched to a CSA based on their census block group at enrollment. CoVPN 5002 participants were matched to a CSA based on the address of the venue in which they enrolled, as their actual physical address was not collected for the study.

Seven continuous CSA-level variables that have previously been associated with forgone care (prior to the COVID-19 pandemic) were included in the community-level analysis of forgone care. All CSA-level data was acquired from the Baltimore Neighborhood Indicators Alliance (BNIA) [ 48 ]. These variables included the below (year of data collection according to BNIA is notated in parenthesis):

• Percent of households with no internet at home (2020): individuals living in communities with poor internet coverage have been found to be less likely to utilize telehealth services offered during the COVID-19 pandemic [ 22 , 23 ].
• Walkability score (2017): individuals living in communities with poor walkability have been found to be associated with decreased healthcare access [ 27 ]. Challenges associated with poor walkability were likely compounded by the COVID-19 pandemic with closures of public transportation and other nearby resources.
• Percent of population that is Hispanic (2020): segregation of ethnic minorities are associated with “place” disparities, including access to healthcare [ 24 ].
• ○ Percentage of households that pay more than 30% of their total household income on rent and related expenses (2020).
• ○ Percentage of 12 th graders in a school year that successfully completed high school (2020/2021).
• ○ Percentage of households whose income fell below the poverty threshold (2020).
• ○ Percentage of population who are not in the labor force (age 16–64 years) (2020).

Covariates.

Two “pandemic wave” binary variables were added to the models to help account for the different enrollment periods of the parent studies and what waves of the pandemic each participant experienced that may have impacted their ability or desire to seek healthcare. All participants who enrolled on or after August 1, 2021 were coded as having experienced the delta COVID-19 wave; those who enrolled on or after December 1, 2021 were coded as having experienced the omicron COVID-19 wave. A binary variable was also created to account for which parent study the data were acquired from.

Statistical analyses

Imputation of missing data..

Patterns of missingness were explored to determine whether data were missing at random. Multiple imputation was then used to impute missing data [ 51 ] using Stata version 16.0 (StatCorp, College Station, TX). The sequential imputation using chained equations method was employed for this study, using the individual-level independent variables, the outcome of forgone care, and “study” variable as predictors of missing values. Five total imputed datasets were created. A sensitivity analysis was conducted at the completion of the model-building process to check for biases introduced during multiple imputation. For the sensitivity analysis, the final model was run using only participants with complete data. The magnitude of the resulting coefficients was then compared with those obtained from running the same model using the imputed dataset.

Model building—Level-one model.

Weighted bivariate logistic regressions were conducted for each individual-level independent variable, with the binary outcome of any type of forgone care. Each observation was weighted in the regression model for the total amount of years the individual had experienced in the pandemic, measured from March 1, 2020 until the date of survey completion. Any individual-level variable significant at p≤0.10 was carried over to the final level-one multivariable model. The multivariable weighted level-one model also included the “study” and “pandemic wave” variables. Collinearity of independent variables was also checked using variation inflation factor, with none noted.

Model building—Level-two multi-level model.

The level-two model included weighted random effects logistic regressions with participants clustered within Baltimore CSAs. The model contained all significant level-one variables, and the level-two continuous community-level variables were tested one at a time. Any CSA-level variables significant at p ≤0.10 were incorporated into the final multivariable model. The significance of variables in this final model were set a p≤0.05.

Power analysis.

A power analysis based on preliminary data assumed an event rate of 0.41 [ 9 , 10 ], an alpha of 0.05, 80% power, an estimated sample size of n = 1,662, and 30 Baltimore CSAs. Assuming these parameters and an intraclass correlation coefficient (ICC) of 0.010, the study was powered to detect odds ratios that ranged from 1.34 to 1.45, as the distribution of the predictor variable ranged from 20/80 split to a 50/50 split.

Ethical considerations

This study was approved by the Johns Hopkins University School of Medicine (JHU SOM) Institutional Review Board (IRB) on December 19, 2022 (IRB# 00348695). The C-Forward parent study was approved by the JHU SOM IRB on June 2, 2020 (IRB# 00250298). The CoVPN 5002 parent study was approved by the JHU SOM IRB on January 28, 2021 (IRB#00262004) through a reliance agreement with Advarra IRB, which was the IRB of record for the larger CoVPN 5002 network study. This secondary data analysis was granted a consent waiver as participants who enrolled in either parent study completed consent forms that covered the conduct of this research. During data analysis, authors of this article had access to a limited dataset provided by the parent study data management teams.

Participant characteristics

Seventy-one percent of C-Forward participants (1,405 of 1,978) met inclusion criteria for this secondary analysis. A slightly smaller percentage of those enrolled in the CoVPN 5002 study (598 of 1,022; 59%) met inclusion criteria. This yielded a total sample size of n = 2,003 (see Fig 1 ). Nearly 65% of the sample reported their sex at birth as female. Most (87.6%) reported not being of Hispanic or Latino origin and 52.7% reported their race as Black or African American. Nearly 40% of the sample reported being married or partnered, slightly less than half (45.1%) were employed part or full-time, and 15.5% reported being on disability status. Twenty percent of participants reported being worried about their ability to pay or being unable to pay their rent or mortgage during the pandemic, nearly 8% reported losing their housing during the pandemic, and 30% reported making less than $25,000 per year. Nearly 65% reported having at least one co-morbidity, including a cancer diagnoses, diabetes, renal disease, sickle cell anemia, respiratory disease, cardiac disease, or immune disease ( Table 1 ).

https://doi.org/10.1371/journal.pone.0302064.t001

In total, 567 participants reported experiencing any type of forgone care. This included 495 participants who reported forgoing chronic or preventive care, 33 participants who reported forgoing emergent care, and 94 participants who reported delaying an elective surgery or dental procedure. Nearly 57% of those who reported forgone care were over the age of 50 years, 67.9% were female, and over half (50.3%) reported being Black of African American.

CSA characteristics

The sample included participants from 48 of the 55 CSAs in Baltimore. The number of participants per CSA ranged from 2 to 174. The calculated ICC was 0.09. Table 2 summarizes the mean and standard deviation values for each of the seven CSA-level variables for those who did and did not report forgone care.

https://doi.org/10.1371/journal.pone.0302064.t002

Correlates of forgone care

Results—individual-level correlates of forgone care..

Table 3 presents the results from the level-one weighted bivariate analyses examining the association of each individual level variable with forgone care. Several pre-disposing factors were found to be associated with forgone care. Those in the age group 35–49 years were found to have a 1.48 higher odds of forgone care, compared to the age group 18–34 (p = 0.001); conversely, those in the ≥65 age group were found to have a 25% lower odds of forgone care, compared to individuals 18–34 years (p = 0.020). The odds of forgone care were also higher in those reporting female sex at birth (OR 1.24, p = 0.010) and those on disability status (OR 1.43, p = 0.001). Individuals reporting Black or African American race had a 15% lower odds of forgone care (p = 0.047).

https://doi.org/10.1371/journal.pone.0302064.t003

Two enabling factors were found to be associated with higher odds of forgone care, including those who reported losing their housing during the COVID-19 pandemic (OR 1.90, p = <0.001) and those who reported being worried about paying their rent or mortgage (OR 1.69, p = <0.001). Finally, significant need level factors with higher odds of forgone care included those with functional limitations (OR 1.66, p<0.001), those with mental illness (OR 1.87, p<0.001), those who reported using substances (OR 1.43, p = 0.004), and those with two or more comorbidities, compared to no comorbidities (OR 1.24, p = 0.023).

Results—Final multivariable model.

The results of the final weighted multivariable model can be found in Table 3 , adjusted for the pandemic wave and study variables and age category, sex, race, disability status, loss of housing, worrying about rent/mortgage, presence of functional limitations, mental illness, substance abuse, and comorbidity number. Predisposing factors that were statistically significant in the final model included those who reported being ages 35–49 years, who were found to have a higher odds of forgone care compared to those in the 18–34 years age group (OR 1.51, p = 0.001). Individuals who reported their sex at birth as female were also found to have higher odds of forgone care, compared to those who reported their sex at birth as male (OR 1.21, p = 0.028). Individuals who reported their race as Black/African American had a 32% reduction in their odds of forgone care, compared to individuals of any other race (OR 0.68, p = ≤0.001). Significant enabling factors included those who reported losing their house during COVID-19, compared to those who did not (OR 1.47, p = 0.014) and those who reported being worried about paying their rent or mortgage, compared to those who were not (OR 1.37, p = 0.005). Need level factors that remained significant in the final model included those with functional limitations, compared to those without (OR 1.46, p = ≤0.001) and those who reported having a mental illness, compared to those without (OR 1.44, p = ≤0.001).

Results—Community-level correlates of forgone care.

None of the continuous CSA-level variables were found to be significant at the p≤0.10 level after controlling for the individual level variables of age category, sex, race, disability status, loss of housing, worrying about rent/mortgage, presence of functional limitations, mental illness, substance abuse, and comorbidity number. Thus, none of the CSA-level variables were added to the model with the individual level factors.

Several studies published during the COVID-19 pandemic on forgone care indicate that economically disadvantaged and historically excluded populations experienced a greater prevalence of forgone care [ 8 – 10 , 12 , 14 , 19 ]. However, few studies have investigated correlates of forgone care that go beyond social and economic factors, such as examining the influence of the local community in which people live. Given the widespread impacts of the COVID-19 pandemic on both individuals and communities, it is important to explore the myriad, multilevel SSDoH that may influence forgone care [ 52 ]. However, our study found that none of the community-level determinants were significantly associated with forgone care in the multilevel model. This finding differs from previously published literature that has identified community-level disparities in COVID-19-related outcomes, although the geographic unit of analyses used in these studies differ from what was used in our study [ 27 – 31 ].

In this racially and economically diverse sample, we found that Black/African Americans living in Baltimore were less likely to experience forgone care, which is in opposition to some previously published work on forgone care during the COVID-19 pandemic [ 10 , 13 , 14 ]. However, this finding was consistent with Tsuzaki & Taira, who found that non-Hispanic/LatinX Black Medicare beneficiaries were less likely to forgo care in the summer of 2020 compared to White beneficiaries [ 16 ]. These findings warrant additional exploration, including comparisons of healthcare utilization practices prior to versus during the pandemic. There are long-standing, systemic inequities in healthcare access and utilization within the Black/African American community that were further exacerbated during the COVID-19 pandemic. For example, a 2016 report by the University of Maryland found that Black/African American Maryland residents were 1.9 times more likely to be unable to afford a visit with a healthcare provider than White residents and were much more likely to die from heart disease, diabetes, stroke, and asthma [ 53 ]. Black/African American individuals included in our study sample may have reported less episodes of forgone care because they have historically experienced systemic barriers to access within the healthcare system. Therefore, they may have been less likely to use the healthcare system even prior to the pandemic, and thus less likely to report forgone care.

In our analysis of individual-level correlates of forgone care, we identified those who have experienced housing insecurity during the pandemic, as evidenced by loss of housing or worrying about paying for housing, as having higher odds of forgone care. Income inequities and financial instability have previously been identified as critical determinants of an individual’s healthcare utilization practices and the experience of forgone care [ 54 ]. Unfortunately, the pandemic impacted the economic stability of millions of American households, particularly lower-income families, and many lost jobs as a result [ 55 ]. This may have drove increased rates of forgone care within individuals experiencing financial hardship and housing instability. Anderson et al., for example, found that 52% of respondents who reported missing medical care did so due to “financial repercussions of the COVID-19 pandemic” [ 9 ]. Notably, several safety net programs, such as the Coronavirus Aid, Relief, and Economic Security (CARES) Act, which provided unemployment benefits and additional financial support to American families, and the continuous Medicaid enrollment provision under the Families First Coronavirus Response Act, were available to qualifying individuals early in the pandemic [ 56 , 57 ]. However, a study published in 2020 on access and enrollment in safety net programs during the pandemic found gaps in awareness for several programs, including health insurance exchanges [ 58 ]. Our study also found that individuals reporting female sex at birth had higher odds of forgone care compared to those reporting male sex at birth. During the pandemic, many women had to take on additional caretaking roles, including homeschooling children and caring for ill family members [ 59 ]. These additional responsibilities may have impacted their ability to seek healthcare when needed. Further, it was well established prior to the pandemic that men seek healthcare less than women [ 60 ], and it is possible this was carried forward in this sample.

The odds of forgone care were also higher in individuals reporting functional limitations. These individuals likely have a higher reliance on support services such as accessible transportation, and interruptions in these services may have disproportionately impacted their ability to access the health system. Those reporting a mental illness also reported an increased odds of forgone care, a finding that aligns with other published COVID-19 forgone care literature [ 12 ]. Individuals suffering from mental illness have previously been shown to be at higher risk for forgone care [ 61 ], and exacerbations in mental health crises during the pandemic may have disproportionately led to the increased risk of forgone care within this population.

In a world where pandemics and other humanitarian emergencies are increasingly likely due to population growth, interactions at the human-animal interface, climate change, and global travel, it is critical that we strengthen models of care so that health systems can continue to support individual and community health during future public health emergencies. One potential strategy is to increase the use of mobile-based healthcare services. Mobile health clinics have previously been shown to be effective in providing urgent care, preventive health, and chronic disease management and have been shown to increase healthcare access for underserved communities, including the economically disadvantaged [ 62 ]. Some of the benefits of mobile health clinics include the elimination of barriers such as lack of transportation, inconvenient operating hours, and long wait times and the ability to form trusting relationships within communities, particularly those who experience stigma such as people living with mental illness [ 62 ]. Furthermore, leveraging mobile clinics in the midst of an emergency have been shown to reduce disruptions in care, as they are already well-integrated into the community and can be effectively and quickly deployed [ 62 ]. Leveraging of mobile clinics during COVID-19 have been captured in the literature to-date. For example, co-location of COVID-19 vaccines within existing harm reduction mobile services has been demonstrated to be an effective way to deliver vaccines to underserved populations [ 63 ]. More widespread use of these types of clinics now and in the future could help reduce forgone care, particularly among those who already experience barriers to healthcare access.

Another strategy that could help address inequities in forgone care during COVID-19 and future health emergencies would be adoption of programs that could extend telehealth services to those who currently lack access. This should include not only the resources required for telehealth, such as internet coverage and smartphones, but also changes in insurance policies that increase coverage and better education for consumers on how to utilize this technology [ 64 ]. For example, participants in one study reported that a major disadvantage of telehealth was their “unfamiliarity” with the platform and distrust that their information was secure and private [ 65 ]. Healthcare providers also expressed gaps in knowledge on how to use telemedicine and what services were covered by insurance [ 65 ], indicating additional opportunities for education to ensure more consistent and widespread use. Additionally, while important policy changes have been implemented to expand telehealth during COVID-19, permanent adoption of some of these changes, such as compensation for primary healthcare services, could help ensure continued access and would already be in place in the event of a new health emergency [ 66 ].

Limitations

This study has several limitations. First, missing data for participants across several independent variables necessitated imputation of missing values for the model-building process, which may have led to biased results. However, a sensitivity analysis using only participants with complete data revealed similar magnitudes of odds ratios for all variables found to have significance at p≤0.05 in the final, imputed dataset. Second, low sample size amongst participants reporting Hispanic/LatinX origin prohibited incorporation into the final model. Third, the different enrollment periods of the parent studies covered different time periods within the pandemic that may have led to forgone care. We have addressed this limitation by using models weighted by years in the pandemic at time of parent study enrollment. Fourth, because the CoVPN 5002 study did not collect participant’s address, we had to assume their residence was within the venue of enrollment. While most venues included low-income housing developments, their assigned CSA may not have been accurately reflected in the data. Fifth, because this study is based upon participant-reported survey data, it may be subject to recall bias. Finally, there is the potential for selection bias which may impact the representativeness of the Baltimore population—for example, the unemployment rate within our sample (52.3%) was higher than that of Baltimore City (29.0%), according to 2021 BNIA data [ 67 ], which may be due to greater representation of individuals from CSAs with higher unemployment rates. However, our final study sample was relatively similar across other characteristics, including sex (study sample-54.5% female; Baltimore-53.1% female), race (study sample-52.7% Black/African American; Baltimore-61.6% Black/African American), ethnicity (study sample-3.7% Hispanic; Baltimore-5.6% Hispanic), and poverty (study sample-30% with income <%25,000 per year; Balitmore-20.3% live below the federal poverty level), when comparing our study sample to 2022 Baltimore census data [ 42 ]. Additionally, the CoVPN 5002 parent study did not collect data on participant’s health insurance status, which likely impacted healthcare utilization. However, it could be inferred to be similar to the 2022 census data (approximately 6.4% of population under age 65 years is uninsured in Baltimore) [ 42 ].

Conclusions

Despite these limitations, this study has important implications for addressing unmet healthcare needs that have occurred during the pandemic. However, additional research will be critical to further understanding how healthcare access and utilization practices differed during versus before the pandemic and to more clearly identify those who are at highest risk of the downstream consequences of forgone care. It is also critical that the health system identify ways to address any new barriers to care that under-resourced populations might be experiencing, such as the increased use of mobile health services or telemedicine platforms. Additionally, moving forward, public health emergency preparedness planning efforts must account for the unique needs of these communities during crises, to ensure that their health needs can continue to be met. This will require additional studies that seek to better understand the perspectives and experiences of these populations during the pandemic, and how models of care can be adapted to serve them better in the future.

Supporting information

S1 file. parent study survey questions..

https://doi.org/10.1371/journal.pone.0302064.s001

Acknowledgments

We would like to acknowledge the participants of the C-Forward and CoVPN 5002 studies for their participation. We would also like to acknowledge the team at the Center for Infectious Disease and Nursing Innovation for their tireless work in recruitment of participants in both of the parent protocols.

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Knowledge, Attitudes and Practices in Travel-related Infectious Diseases: The European Airport Survey

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Koen Van Herck, Francesco Castelli, Jane Zuckerman, Hans Nothdurft, Pierre Van Damme, Atti-La Dahlgren, Panagiotis Gargalianos, Rogelio Lopéz-Vélez, David Overbosch, Eric Caumes, Eric Walker, Sandra Gisler, Robert Steffen, Knowledge, Attitudes and Practices in Travel-related Infectious Diseases: The European Airport Survey, Journal of Travel Medicine , Volume 11, Issue 1, 1 January 2004, Pages 3–8, https://doi.org/10.2310/7060.2004.13609

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The European Travel Health Advisory Board conducted a cross-sectional pilot survey to evaluate current travel health knowledge, attitudes and practices (KAP) and to determine where travelers going to developing countries obtain travel health information, what information they receive, and what preventive travel health measures they employ. Subsequently, the questionnaire used was improved and a cross-sectional, multicenter study was undertaken in airports in Europe, Asia, South Africa and the United States. This paper describes the methods used everywhere, and results from the European airports.

Between September 2002 and September 2003, 5,465 passengers residing in Europe and boarding an intercontinental flight to a developing country were surveyed at the departure gates of nine major airports in Europe. Questionnaires were self-administered, and checked for completeness and validated by trained interviewers.

Although the majority of travelers (73.3%) had sought general information about their destination prior to departure, only just over half of the responders (52.1%) had sought travel health advice. Tourists and people traveling for religious reasons had sought travel health advice more often, whereas travelers visiting friends and relatives were less likely to do so. Hepatitis A was perceived as the most probable among the infectious diseases investigated, followed by HIV and hepatitis B. In spite of a generally positive attitude towards vaccines, 58.4% and 68.7% of travelers could not report any protection against hepatitis A or hepatitis B, respectively. Only one in three travelers to a destination country with at least some malaria endemicity were carrying antimalarial drugs. Almost one in four travelers visiting a high-risk area had an inaccurate risk perception and even one in two going to a no-risk destination were unnecessarily concerned about malaria.

The large variation in destinations, age of the travelers and reasons for traveling illustrates that traveling to a developing country has become common practice. The results of this large-scale airport survey clearly demonstrate an important educational need among those traveling to risk destinations. Initiatives to improve such education should target all groups of travelers, including business travelers, those visiting friends and relatives, and the elderly. Additionally, travel health advice providers should continue their efforts to make travelers comply with the recommended travel health advice. Our common objective is to help travelers stay healthy while abroad, and consequently to also reduce the potential importation of infectious diseases and the consequent public health and other implications.

World Health Organization. International travel and health 2003 Geneva WHO .

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Schlagenhauf P Steffen R Tschopp A et al. Behavioural aspects of travelers in their use of malaria presumptive treatment . Bull World Health Organ 1995 ; 73 : 215 – 221 . 7743593

Schunk M Wachinger W Nothdurft HD . Vaccination status and prophylactic measures of travelers from Germany to subtropical and tropical areas: results of an airport survey . J Travel Med 2001 ; 8 : 260 – 262 . 11703909

Steffen R Fuchs E Schildknecht J et al. Mefloquine compared with other malaria chemoprophylactic regimens in tourists visiting East Africa . Lancet 1993 ; 341 : 1299 – 1303 . 8098447

Steffen R Collard F Tornieporth N et al. Epidemiology, etiology, and impact of traveler's diarrhea in Jamaica . JAMA 1999 ; 281 : 811 – 817 . 10071002

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Zuckerman J . Shaping travel health and medicine for the future . Lancet Infect Dis 2001 ; 1 ( 5 ): 296 – 297 . 11871801

This study was funded by the European Travel Health Advisory Board (ETHAB), which had an unrestricted educational research grant from GlaxoSmithKline Biologicals (Rixensart, Belgium) and Novartis (Basle, Switzerland).

• antimalarials
• hepatitis a
• hepatitis b
• communicable diseases
• developing countries
• self administration
• south africa
• knowledge acquisition
• public health medicine
• older adult
• risk perception
• positive attitude

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