Practical Insights for Public Health Decision-Makers: Using Time Series Models with NTD Disease Counts (Selected) for Myanmar, Nepal, and Timor-Leste

The effort to provide medical and public health services in order to eliminate (or bring to near-zero) the burden of neglected tropical diseases (NTDs) on global populations is a public health issue that can be aided through managerial epidemiologic practice. The use of epidemiology (including statistical methods) to study the health history of a population, diagnose the health of a community, and/or examine the work of health services can be enacted in a way to better understand the health status of a population and matters related to health service utilization within a population or community. This paper describes the use of time series methods from managerial epidemiology to provide additional insights for public health decision-makers seeking to reduce NTD counts in the WHO South-East Asia Region, specifically, the countries of Myanmar, Nepal, and Timor-Leste. The examination of leprosy and visceral leishmaniasis disease counts for the three countries revealed interesting patterns. ARIMA models were used and included the calculation of the 95% CI around forecasted values that had public health significance for public health decision-makers. An important consideration for these decision-makers is to take steps that will control specific neglected tropical diseases and not allow the diseases to get out of control. Keywords: Neglected tropical diseases; managerial epidemiology; ARIMA time series; public health decision-makers; public health workforce