Modelling the Dynamics and Optimal Control of Schistosomiasis Transmission Under Climate Change

Abstract

Neglected tropical diseases (NTDs) are estimated to affect at least 1.65 billion people annually in rural areas and in some low-income urban settings of developing countries. These diseases are widely disregarded by global funding agencies as opposed to other infectious diseases such as HIV-AIDS and malaria, which have received substantial support, funding, and other resources. Although these "higher-profile" diseases cause substantially more deaths than NTDs annually, NTDs constitute substantial threats to the health, social, and economic development of affected countries and particularly to populations living under resource-limited conditions. This is especially true for schistosomiasis, a waterborne, parasitic disease that affects more than 250 million people worldwide with more than 700 million people living in endemic areas across more than 78 countries in Africa, Asia, and Latin America and is considered one of the most prevalent parasitic diseases, ranking second after malaria. Because schistosomiasis is primarily transmitted by intermediate snail hosts whose reproduction and development depend heavily on the conditions of the surrounding environment, the changes in temperature, annual precipitation, and other environmental and climatic factors projected by climate change are heavily relevant to the study of how schistosomiasis distribution will evolve in the future, which is in turn, valuable information in formulating long-term sustainable disease control plans. Determining the exact effects of global climate and environmental change on schistosomiasis transmission and prevalence distribution is still a largely open question in the scientific community as it has proven to be difficult due to its complex nature. In this study, we contribute to the understanding of the effect of global climate and environmental change on schistosomiasis by implementing a hybrid approach to model the change in global infection distribution under climate change projections and construct a financial framework for control strategies to begin the study on how to construct programs to mitigate the changes in transmission brought about by climate change.