Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data

Abstract

Background Leptospirosis is among the leading zoonotic causes of morbidity and mortality worldwide. Knowledge about spatial patterns of diseases and their underlying processes have the potential to guide intervention efforts. However, leptospirosis is often an underreported and misdiagnosed disease and consequently, spatial patterns of the disease remain unclear. In the absence of accurate epidemiological data in the urban agglomeration of Santa Fe, we used a knowledge-based index and cluster analysis to identify spatial patterns of environmental and socioeconomic suitability for the disease and potential underlying processes that shape them. Methods We geocoded human leptospirosis cases derived from the Argentinian surveillance system during the period 2010 to 2019. Environmental and socioeconomic databases were obtained from satellite images and publicly available platforms on the web. Two sets of human leptospirosis determinants were considered according to the level of their support by the literature and expert knowledge. We used the Zonation algorithm to build a knowledge-based index and a clustering approach to identify distinct potential sets of determinants. Spatial similarity and correlations between index, clusters, and incidence rates were evaluated. Results We were able to geocode 56.36% of the human leptospirosis cases reported in the national epidemiological database. The knowledge-based index showed the suitability for human leptospirosis in the UA Santa Fe increased from downtown areas of the largest cities towards peri-urban and suburban areas. Cluster analysis revealed downtown areas were characterized by higher levels of socioeconomic conditions. Peri-urban and suburban areas encompassed two clusters which differed in terms of environmental determinants. The highest incidence rates overlapped areas with the highest suitability scores, the strength of association was low though (CSc r = 0.21, P < 0.001 and ESc r = 0.19, P < 0.001). Conclusions We present a method to analyze the environmental and socioeconomic suitability for human leptospirosis based on literature and expert knowledge. The methodology can be thought as an evolutive and perfectible scheme as more studies are performed in the area and novel information regarding determinants of the disease become available. Our approach can be a valuable tool for decision-makers since it can serve as a baseline to plan intervention measures.

Towards a leptospirosis early warning system in northeastern Argentina

“…First, spatially aggregated data mask the effects of hydrometeorological drivers of disease at finer spatial scales. A recent analysis of the spatial distribution of leptospirosis suitability in Santa Fe province has shown that there is marked difference with elevation, urban and suburban structure, and environmental conditions [ 30 ]. Most leptospirosis cases were reported in the largest cities and in some of them there are other water bodies, such as the Salado River in Santa Fe.…”

Analysis of Distribution Patterns of Environmental Risk Factors with Malaria Incidents in the Working Area of the Tanjung Tiram Community Health Center, Batu Bara Regency

“…Distribution pattern analysis functions to determine spatial variations, both in the incidence of a disease and its risk factors. With spatial analysis, a mapping process can be Vol 6 carried out to determine the geographic distribution of potential disease risks and their relationship with existing environmental risk factors (Cristaldi et al, 2022). Based on malaria elimination data, in 2014 in North Sumatra province 15 out of 33 districts/cities had received malaria elimination certificates.…”