Changes in environmental epidemiology research methods due to COVID-19

Abstract

BACKGROUND AND AIM: The obligatory pivot to digital research methods during the pandemic has illustrated its advantages in terms of flexibility, efficiency, broader geographic coverage, and lower barriers to participation. Digital research methods are likely to continue to expand in the post-COVID-19 era, although not without challenges and tradeoffs. The digital divide will become an increasingly complex source of selection bias, with important implications for participation of older individuals or those with lower socioeconomic position. For example, online questionnaires used heavily in the early stages of the pandemic, often had limited researcher control over who participated and little information on potentially large selection biases. METHODS: The pandemic has highlighted the potential of big data for public health protection. High-resolution geo-located data, increasingly available through either top-down (i.e. government surveillance) or bottom-up (i.e. volunteered geographic information) sources, paired with spatial analysis, are providing unprecedented opportunities to monitor complex phenomena such as human mobility and interactions. COVID-19 is proving an important impetus for new methods development to deal with complex spatio-temporal data structures with promising applications in environmental epidemiology. RESULTS:Research methods during COVID-19 shifted heavily towards remote biological sample collection, influencing the type and volume of samples collected. This shift is pushing development of improved analytical techniques for small volume samples. While remote collection offers several advantages over laboratory tests that could reduce selection bias (e.g. increased convenience and accessibility for participants living far from a lab), there are important challenges in ensuring data quality during the collection and handling of samples. CONCLUSIONS:In conclusion, the application of methods for conducting research that were a necessity during the COVID-19 pandemic because of the risk of infection can be expected to accelerate. The pandemic has triggered the development of creative, flexible research methods that offer advantages outside of the pandemic context; however, careful consideration of drawbacks is essential. KEYWORDS: COVID-19, big data, environmental epidemiology