Bio-climatic impact on malaria prevalence in Ghana

A multi-scale spatial modeling

Bibliographic Data

ID21835581
AuthorsMoses Asori (0000-0002-1438-4020, Kwame Nkrumah University of Science and Technology, corresponding author), Ali Musah (0000-0002-8615-593X, Kwame Nkrumah University of Science and Technology), Razak M Gyasi (0000-0002-6733-1539, African Population and Health Research Center)
Year2024
Volume43
Issue2
Pages207-228
Publication date2024-02-23
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAfrican Geographical Review (JOURNAL)
Journal identifiersISSN: 1937-6812 • E-ISSN: 2163-2642
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/19376812.2022.2130378
OpenAlexW4304014206
LanguageEN
Citations received1
References cited42

Whilst climate change is expected to tremendously influence the regional transmission of malaria, the available data reveal conflicting results. This study provides contextual evidence. We adopted multi-scale geographically weighted regression (MGWR) modelling approach. AICc and local r2 were used to evaluate performance of the MGWR. . The MGWR analysis showed that LST (β = −0.667), maximum temperature (β = −0.507), mean temperature (β = −0.480), and distance from streams (β = −0.487) were negatively associated with malaria prevalence. However, enhanced vegetation index correlated positively with malaria prevalence (β = 0.663). Our results may be important for public health interventions

Biology · Cartography · Climatology · Economics · Environmental health · Geography · Malaria · Socioeconomics · Spatial ecology · COVID-19 epidemiological studies · Medicine · Species Distribution and Climate Change · Zoonotic diseases and public health · Ecology · Geology · Immunology

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