A Comparative Analysis of Methodological Approaches Used for Estimating Risk in Travel Medicine: Table 1

Providing optimal pretravel advice requires travel medicine practitioners to perform an epidemiologic and host‐related risk assessment so that preventive measures can be appropriately prioritized for each traveler.1,2 Individual host characteristics and itinerary details must be considered to properly balance the efficacy, side effects, and costs of various interventions against estimates of the incidence and severity of the disease(s) they can prevent. Most preventable travel‐related diseases are associated with relatively low risks, generally of the order of 1 of 100,000 to 100 of 100,000. Consequently, decisions regarding intervention measures that minimize risks will depend on the risk threshold, such that diseases with poor or fatal outcomes will undoubtedly be associated with less tolerance of even small risks than diseases leading to only mild morbidity. The patient’s own perception of risk and their attitude toward the reassurance provided by the intervention measure versus its potential side effects or costs is also a vital consideration when tailoring individual pretravel advice. Research providing data on the risk factors for specific adverse health outcomes during travel enables high‐risk travelers to be identified and preventive measures to be optimally targeted.1 In addition to benefiting risk management in the individual traveler, improved understanding of the health risks faced according to individual traveler characteristics and itineraries and up‐to‐date data regarding the epidemiology of specific infections also provide guidance regarding possible differential diagnoses following travel to specific areas. This facilitates assessment and quantification of disease risks if a traveler returns with an illness and helps guide diagnostic measures and rapid empiric treatment interventions. Reliable data regarding the burden of travel‐related illness also have the potential for significant public health impact by facilitating the recognition and limitation of disease transmission across international borders. Until recently, the evidence base for travel recommendations has largely relied on case reports, case series, retrospective chart reviews, or small single‐institution cross‐sectional or cohort studies. Many reports have been retrospective, often citing opportunistic rather than systemically collected data. These studies have helped to establish the groundwork for travel‐related research and to suggest risk factors associated with common adverse health outcomes among travelers. However, there are limitations and biases associated with each research approach that can significantly impact risk estimates, and results of risk estimate studies performed among limited populations or involving limited travel destinations will often not be generalizable to other travelers. Some issues regarding the advantages and limitations of different research approaches are similar in travel medicine as in other fields, but the fact that travelers generally have a defined and identifiable period of risk—namely their trip—results in some unique issues for travel researchers. This paper tracks how different methodological approaches that have evolved over the past three decades have contributed to risk characterization and risk estimates in travel medicine. The attack rate of illness following travel to a particular region is expressed as the ratio of travelers to that destination who became ill to the total number visiting that destination. In practice, ascertainment of exact numerators of all incident cases of infection over a time period or of denominators reflecting the total numbers of travelers to each region is difficult to obtain for all diseases. Additionally, disease risks are not stable over time and new infections continue to emerge,3–5 yet for many pathogens, data regarding the incidence of infection in travelers are based on figures collected almost 25 years ago. Furthermore, travel‐related data are nonexistent or scarce for some existing vaccine‐preventable diseases, and new interventions such as vaccines for dengue and hepatitis E are being developed, so establishing evidence‐based recommendations for appropriate implementation of these interventions requires more precise risk evaluation. The short incubation period for many travel‐related infections means that travel researchers often focus health outcomes studies on the first few months following a trip. While rapid symptom onset following exposure is advantageous in enabling the period required for follow‐up of patients post‐travel to be relatively brief, it also means that current approaches to risk identification may miss infections with long incubation periods. Additionally, the fact that many symptoms occur during a trip can make it difficult for researchers situated in the patients’ home country to make an accurate diagnosis of illness. Another problem is that attribution of place of exposure to determine the incremental risks associated with visiting a specific destination can be problematic, particularly if the itinerary has included multiple countries, if several trips have been undertaken within a relatively short period, or if diseases with delayed symptom onset are being examined. Researchers often present results according to regions of exposure in an attempt to overcome the problem of assigning risk to a particular country; however, exposure risks will not be uniform throughout an entire country let alone an entire region. Similarly, the incremental effect of travel duration as a risk factor for disease acquisition can be difficult to assess, particularly if areas with variable disease endemnicity have been visited. There may be a temptation to use surveillance data of disease risks among endemic populations to infer risks to travelers, but such data may not be particularly relevant to the traveling population as vaccination status, behaviors, and exposures may be markedly different. For example, notifications of Japanese encephalitis occurring among local populations may be impacted by high levels of immunity from widespread vaccination or previous infection, resulting in few reported cases despite ongoing circulation of viruses and limiting the applicability of these data in making vaccine recommendations for travelers. It is important to recognize and understand the strengths and limitations of the major study designs when interpreting individual study results. These are discussed here, with additional information shown in Table 1. Research approaches for risk estimation and risk characterization Research approaches for risk estimation and risk characterization Many retrospective chart reviews and prospective collation of case series have been performed as they are relatively cheap and easy to do. These studies often collate information on unwell travelers who present for medical care to describe the spectrum of diseases seen and analyze the relative frequency of different illnesses. Sometimes, they are limited to individuals returning from a single destination, so that common adverse health outcomes following exposure in that region can be identified. Sometimes, data are collected by clinics that travelers frequent during travel, as these clinics may see a different spectrum of illnesses (often those with short incubation periods), and they can provide focused country‐specific risk information.20,21 Alternatively, case series may focus on a specific disease outcome, collating patients who have developed that illness to identify factors that contribute to risk, such as common demographic or itinerary characteristics. A case‐control study approach is also sometimes performed on accumulated data to better define and delineate observed risk factors. However, there are a number of limitations to this approach. Chart reviews and case series are typically performed by a single institution, so results are influenced by the characteristics, behaviors, and travel destinations favored by its travelers, which limits the generalizability of results. To adequately examine one specific disease etiology, studies often need to be conducted in large referral centers that have accumulated many cases of the disease, and even if sufficient case numbers are available for analysis, such studies will be prone to referral bias. Also, separate destinations and disease outcomes need to be studied one at a time. Additionally, these studies frequently include only unwell—often hospitalized—patients, so they generally reflect only the more severe cases of travel‐related health problems rather than the spectrum of morbidity resulting from travel infections, and comparisons cannot be made between unwell travelers who have presented for medical care and those who have remained well. Some of these issues may be able to be addressed via systematic reviews or meta‐analyses that collate and examine data obtained by a number of institutions; however, some biases and limitations will remain. Finally, these studies lack accurate numerator or denominator data and so cannot inform absolute risk calculations. As an example of this approach, a number of studies by individual centers have focused on travelers returning with fever and have reported on the contribution of malaria as the underlying cause. Results have varied from 27% to 75%22–25 depending on the makeup of the traveling population served by the center, whether all patients seen or only inpatients were included, and according to the common destinations visited by patients from each site. Nevertheless, collectively these studies have enabled examination of a large number of febrile travelers who required medical care and have highlighted the importance of malaria infection. Another example that demonstrates the utility of this research approach is a large study of schistosomiasis performed by a single center in Britain.26 Common symptoms, investigation findings, treatment effects, and follow‐up difficulties among more than 1,100 travelers and immigrants from Africa with schistosomiasis were described. Few study centers could accumulate such large numbers of cases, and it is likely that the major findings are applicable to other travelers from Africa returning to other sites around the world. However, comparative morbidity analyses and examination of other disease outcomes would require additional studies. Cross‐sectional studies involve administration of a questionnaire to a sample population to collect information regarding the prevalence of specific exposures or conditions at one time point. In travel medicine, cross‐sectional studies have often been performed as airport surveys, enabling capture of both ill and well travelers for study. These studies provide estimates of the frequency of exposures among those with and without symptoms, therefore enabling characterization of likely risk factors for illness. They can also estimate the incidence of illnesses that have short incubation periods and therefore occur during travel and can be used to compare attack rates for these acute infections following travel to different destinations. Cross‐sectional studies have also often been used to determine people’s knowledge and practices associated with certain preventive measures. However, this approach has limited utility for estimating risks of infections for which symptom onsets are delayed and the generalizability of findings is limited to the specific population, region, and time period being examined, and these studies are also subject to selection bias as people participating in the study may not be representative of the entire travel population. An example of the contribution this study design can have on risk estimates of illness following travel in different countries is evident in a large, multicenter cross‐sectional survey conducted to examine travelers’ diarrhea among 73,630 short‐term visitors completing airport surveys just prior to flying home from Kenya, India, Jamaica, or Brazil.27,28 Diarrhea was reported by a high of 55% in Mombasa and a low of 14% in Fortaleza, and calculated 14‐day incidence rates varied between 20 and 66% according to destination. This highlights the differences in results according to itinerary and suggests that similar studies in other airports would be required to obtain globally comparative data. Another series of cross‐sectional surveys were conducted among travelers departing from a number of different geographical locations (Australasia,29 Europe,30,31 the United States,32 and South Africa33 ) assessing the knowledge, attitudes, and practices of travelers from different regions in relation to travel‐related diseases and preventive measures. The proportion of responders who had sought pretravel health advice ranged from 32% to 86% between the different sites, thereby highlighting the limited generalizability of single‐site cross‐sectional studies of pretravel practices. Cohort studies in travel medicine generally involve recruitment of people undergoing a pretravel health assessment and then follow‐up of these people on return to determine the magnitude and types of adverse health outcomes that occurred. As cohort studies are often questionnaire based, they are essentially the same as longitudinal surveys. This strategy enables determination of the comparative frequency of various illnesses after travel and can highlight risk factors associated with acquisition of different infections. It is also the most common methodological approach for providing incidence estimates of illness since both numerator and denominator data are captured. Cohort studies generally focus on syndromes (eg, travelers’ diarrhea or respiratory symptoms) rather than on specific etiological diagnoses (eg, confirmed influenza), as enormous studies are required to obtain sufficient numbers of each etiological diagnosis for risk calculations. As the source for recruitment of participants is often via a pretravel clinic, these studies are prone to self‐selection bias as not all at‐risk travelers present for pretravel advice. In fact, it is probable that those most at risk, namely, young or budget travelers, are the least likely of all to seek pretravel advice. Additionally, cohort studies are often performed at a single site or may focus on travelers visiting specific high‐risk destinations, and these factors can limit generalizability of results. Most prospective cohort studies have followed patients for the first 3 to 6 months after return and therefore are unable to determine attack rates of diseases with longer incubation periods. 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