Identifying Nontraditional Epidemic Disease Risk Factors Associated with Major Health Events from World Health Organization and World Bank Open Data

Abstract

Health events emerge from host, community, environment, and pathogen factors-forecasting epidemics is a complex task. We describe an exploratory analysis to identify economic risk factors that could aid epidemic risk assessment. A line list was constructed using the World Health Organization Disease Outbreak News (2016-2018) and economic indicators from the World Bank. Poisson regression employing forward imputations was used to establish relationships with the frequency with which countries reported public health events. Economic indicators demonstrated strong performance appropriate for further assessment in surveillance programming. In our analysis, three economic indicators were significantly associated to event reporting: how much the country's urban population changed, its average forest area, and a novel economic indicator we developed that assessed how much the gross domestic product changed per capita. Other economic indicators performed less well: changes in total, female, urban, and rural population sizes; population density; net migration; change in per cent forest area; total forest area; and another novel indicator, change in percent of trade as a fraction of the total economy. We then undertook a further analysis of the start of the current COVID-19 pandemic that revealed similar associations, but confounding by global disease burden is likely. Continued development of forecasting approaches capturing information relevant to whole-of-society factors (e.g., economic factors as assessed in our study) could improve the risk management process through earlier hazard identification and inform strategic decision processes in multisectoral strategies to preventing, detecting, and responding to pandemic-threat events.

Figure 1.

Risk signal identification and input effect on the risk management process. This figure appears in color at www.ajtmh.org.

Figure 2.

Overview of the reported health events in the WHO Disease Outbreak News (2016–2018). Economic indicators were tested against the frequency with which a particular country reported a health event meriting a WHO Disease Outbreak News release, a mechanism of International Heath Regulations (2005) compliance. This figure provides an overview of the distribution and dominant event types that constituted that dataset. (A) Geographic heat map displaying the frequency of health events reported by country. (B) Frequency of the most common of the pathogens/diseases reported. This figure appears in color at www.ajtmh.org.

Figure 3.

Monte Carlo simulation output using Poisson equation regression model. (A) Correlation tornado chart for input variables: gross domestic product change per capita, population change and average forest area. (B) Probability density chart of health event frequency; reference probability values were placed at 0.0 and 1.0 events. This figure appears in color at www.ajtmh.org.