Abstract
Background
Malaria control programs throughout much of the Pan American Health Organization (PAHO) region have been shifting their focus towards malaria elimination. Maximizing resources, particularly by making the most of passive and active surveillance data, is critical to this effort. Defining fine scale spatial targets that consider epidemiologic, environmental, and social factors will facilitate a contextualized response that increases cost efficiency as well as intervention effectiveness.
As a proof of concept, this pilot study focused on the municipality of Guapi, department of Cauca, located on the Colombian Pacific coast, an endemic area with the highest disease burden in Plasmodium falciparum malaria, where gold mining and deforestation result in dynamic, unstable, and heterogeneous malaria transmission.
Methods
Spatial analysis was performed using epidemiological surveillance data at the individual - and collective levels in the municipality of Guapi in 2020 and used spatial statistics to identify hotspots of elevated risk. Multivariate analysis was
conducted on selected sociodemographic, ecological, and epidemiologic variables to better understand the drivers of risk in the region, with geographic weighted regression used to yield spatial maps of intervention targets.
Findings
Malaria cases in urban areas were concentrated in 38% (8) endemic neighborhoods shouldering a high burden of disease , with additional clusters of disease in rural coastal and inland river areas. Statistically significant malaria
clusters were identified along a gradient of land use/land cover, including the central urban area, pacific mangrove forests, and inland at the confluence of the Guapi and Napi rivers. These clusters represent three ecologically distinct regions, suggesting, similarly, that disparate determinants are at play in driving transmission dynamics in each area. These distinctions are potentially anthropomorphic, with human social and behavioral variation from urban to rural areas, the role mining activities plays in malaria transmission, as well raises questions regarding the role spatial distribution of Anopheles species from the coastally-distributed Anopheles albimanus, the urban-adapted Anopheles
nuneztovari, and the river-dwelling Anopheles darlingi has in the clustering of malaria cases.
Interpretation
Geospatial analysis yielded significant spatial targets for malaria intervention efforts to achieve elimination goals , not just of concentrations of disease transmission, but also the variation in spatial distribution of transmission drivers.
This study demonstrates the utility of adding geospatial analysis to the analytic protocol for reviewing malaria surveillance data
Malaria control programs throughout much of the Pan American Health Organization (PAHO) region have been shifting their focus towards malaria elimination. Maximizing resources, particularly by making the most of passive and active surveillance data, is critical to this effort. Defining fine scale spatial targets that consider epidemiologic, environmental, and social factors will facilitate a contextualized response that increases cost efficiency as well as intervention effectiveness.
As a proof of concept, this pilot study focused on the municipality of Guapi, department of Cauca, located on the Colombian Pacific coast, an endemic area with the highest disease burden in Plasmodium falciparum malaria, where gold mining and deforestation result in dynamic, unstable, and heterogeneous malaria transmission.
Methods
Spatial analysis was performed using epidemiological surveillance data at the individual - and collective levels in the municipality of Guapi in 2020 and used spatial statistics to identify hotspots of elevated risk. Multivariate analysis was
conducted on selected sociodemographic, ecological, and epidemiologic variables to better understand the drivers of risk in the region, with geographic weighted regression used to yield spatial maps of intervention targets.
Findings
Malaria cases in urban areas were concentrated in 38% (8) endemic neighborhoods shouldering a high burden of disease , with additional clusters of disease in rural coastal and inland river areas. Statistically significant malaria
clusters were identified along a gradient of land use/land cover, including the central urban area, pacific mangrove forests, and inland at the confluence of the Guapi and Napi rivers. These clusters represent three ecologically distinct regions, suggesting, similarly, that disparate determinants are at play in driving transmission dynamics in each area. These distinctions are potentially anthropomorphic, with human social and behavioral variation from urban to rural areas, the role mining activities plays in malaria transmission, as well raises questions regarding the role spatial distribution of Anopheles species from the coastally-distributed Anopheles albimanus, the urban-adapted Anopheles
nuneztovari, and the river-dwelling Anopheles darlingi has in the clustering of malaria cases.
Interpretation
Geospatial analysis yielded significant spatial targets for malaria intervention efforts to achieve elimination goals , not just of concentrations of disease transmission, but also the variation in spatial distribution of transmission drivers.
This study demonstrates the utility of adding geospatial analysis to the analytic protocol for reviewing malaria surveillance data
| Original language | American English |
|---|---|
| State | Published - 2023 |
| Event | Consortium of Universities for Global Health Annual Conference - Washington, United States Duration: Apr 14 2023 → Apr 16 2023 Conference number: 13th |
Conference
| Conference | Consortium of Universities for Global Health Annual Conference |
|---|---|
| Abbreviated title | CUGH2022 |
| Country/Territory | United States |
| City | Washington |
| Period | 4/14/23 → 4/16/23 |
Funding
| Funders | Funder number |
|---|---|
| The FIU Foundation and Office of Research and Development |