Spatial Targeting of Adaptive Social Protection in South Asia: An Analysis of Climate-Economy-Disease Hotspots and Policy Gaps

<title>Abstract</title> <p>Climate elements, economic conditions, and vector-borne diseases are associated with one another. However, existing research has not sufficiently investigated the simultaneous spatiotemporal patterns of these three factors. This study aims to examine these together, focusing on South Asia, which is particularly vulnerable to them. Specifically, it visualizes regions where climate, economic, and disease stresses overlap spatiotemporally as overlapping hotspots, compares these hotspots with existing policy coverage to identify policy gaps, and proposes how Adaptive Social Protection (ASP), as a policy framework that addresses these three stresses, can be implemented. Understanding this is significant for providing evidence to implement equitable and shock-responsive policies in a data-driven manner that would help address sustainable development goals (SDGs). We created an analytical data frame at the administrative area level 1 (ADM1) by including all but one South Asian Association for Regional Cooperation (SAARC) countries from 2012 to 2022 by merging monthly data on temperature, precipitation, nighttime light, and dengue fever from open data sources. Robust stress variables are built, typified, and hotspot analysis is conducted based on the contiguity and spatial correlation of stress variables. Combining classification of regions and hotspot analysis results enabled the identification of areas experiencing sustained high stress levels, which are otherwise difficult to capture within a single sector. Furthermore, these hotspots are compared with existing policy documents at the country-level (ADM0), thereby allowing analysis of policy prioritization. Based on this assessment, policy implications, including the spatial targeting of ASP, are suggested for each country in the SAARC region.</p>