Infectious Disease Underreporting Is Predicted by Country-Level Preparedness, Politics, and Pathogen Severity

Abstract

Underreporting of infectious diseases is a pervasive challenge in public health that has emerged as a central issue in characterizing the dynamics of the COVID-19 pandemic. Infectious diseases are underreported for a range of reasons, including mild or asymptomatic infections, weak public health infrastructure, and government censorship. In this study, we investigated factors associated with cross-country and cross-pathogen variation in reporting. We performed a literature search to collect estimates of empirical reporting rates, calculated as the number of cases reported divided by the estimated number of true cases. This literature search yielded a dataset of reporting rates for 32 pathogens, representing 52 countries. We combined epidemiological and social science theory to identify factors specific to pathogens, country health systems, and politics that could influence empirical reporting rates. We performed generalized linear regression to test the relationship between the pathogen- and country-specific factors that we hypothesized could influence reporting rates, and the reporting rate estimates that we collected in our literature search. Pathogen- and country-specific factors were predictive of reporting rates. Deadlier pathogens and sexually transmitted diseases were more likely to be reported. Country epidemic preparedness was positively associated with reporting completeness, while countries with high levels of media bias in favor of incumbent governments were less likely to report infectious disease cases. Underreporting is a complex phenomenon that is driven by factors specific to pathogens, country health systems, and politics. In this study, we identified specific and measurable components of these broader factors that influence pathogen- and country-specific reporting rates and used model selection techniques to build a model that can guide efforts to diagnose, characterize, and reduce underreporting. Furthermore, this model can characterize uncertainty and correct for bias in reported infectious disease statistics, particularly when outbreak-specific empirical estimates of underreporting are unavailable. More precise estimates can inform control policies and improve the accuracy of infectious disease models.

Compliance of Primary Healthcare Workers in Saudi Arabia With the National Surveillance System of Tropical and Non-tropical Dermatological Diseases

“…Moreover, as per the current study participants, the high workload was the justification behind the low compliance with reporting. However, these findings have frequently been reported in previous studies [ 17 , 18 ] and demonstrate the need for leader support to address these ongoing issues from the related authority.…”

“…Infectious disease underreporting is a major challenge for any surveillance system. Previous research [ 17 ] attributed that to various reasons, including undetectable asymptomatic diseases, substandard public health infrastructures, and government censorship. Similar to other studies' findings [ 11 , 18 ], the vast majority (88%) of participants in the current study did not report any infectious diseases, though they worked at primary healthcare facilities where it was expected to encounter a variety of infectious cases that required reporting.…”

Evaluation of the Global Health Security Index as a predictor of COVID-19 excess mortality standardised for under-reporting and age structure

“…Therefore, populations with a larger proportion of elderly people have increased vulnerability to severe COVID-19 disease 20–23. A country’s underlying risk for severe illness may also play a role in how likely infections are to be detected,24 as disease severity has been shown to influence whether diseases will be detected in surveillance efforts 25. Thus, in assessing country-level differences in mortality during the pandemic, it is critical to adjust for differences in age structures.…”

Epidemic intelligence activities among national public and animal health agencies: a European cross-sectional study

“…Enhancing cross-border and international collaborations in order to tackle under-reporting and increase early detection, warning and response should be at the centre of future initiatives, taking into account disease-(severity, mode of transmission) and country-speci c (public health infrastructure, epidemic preparedness, politics) factors previously identi ed by evaluations of the sensitivity of international epidemic intelligence tools (27,30).…”