Associations between environmental covariates and malaria incidence in high transmission settings of Uganda: A distributed non-linear lagged ecological analysis
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Research Square
Abstract
Environmental factors such as temperature, rainfall, and vegetation cover play a critical role
in malaria transmission. However, quantifying the relationships between environmental factors and
measures of disease burden relevant for public health can be complex as effects are often non-linear and
subject to temporal lags between when changes in environmental factors lead to changes in the
incidence of symptomatic malaria. The study aim was to investigate the associations between
environmental covariates and malaria incidence in high transmission settings of Uganda.
Methods This study leveraged data from seven malaria reference centres (MRCs) located in high
transmission settings of Uganda over a 24-month period (January 2019 - December 2020). Estimates of
monthly malaria incidence (MI) were derived from MRCs’ catchment areas. Environmental data including
monthy average measures of temperature, rainfall, and normalized difference vegetation index (NDVI)
were obtained from remote sensing sources. A distributed non-linear lagged model was used to
investigate the quantitative relationship between environmental covariates and malaria incidence.
Results Overall, the median (range) monthly temperature was 30oC (26-47), rainfall 133.0 mm (3.0-247),
NDVI 0.66 (0.24-0.80) and MI was 790 per 1000 person-years (73-3973). A non-linear relationship
between environmental covariates and malaria incidence was observed. An average monthly temperature
of 35oC was associated with significant increases in malaria incidence compared to the median observed
temperature (30oC) at month lag 2 (IRR: 2.00, 95% CI: 1.42-2.83) and the cumulative increases in MI
significantly at month lags 1-4, with the highest cumulative IRR of 8.16 (95% CI: 3.41-20.26) at lag month
4. An average monthly rainfall of 200mm was associated with significant increases in malaria incidence
compared to the median observed rainfall (133mm) at lag month 0 (IRR: 1.24, 95% CI: 1.01-1.52) and the
cumulative IRR increases of malaria at month lags 1-4, with the highest cumulative IRR of 1.99(95% CI:
1.22-2.27) at lag month 4. An average NVDI of 0.72 was associated with significant cumulative increases
in IRR of malaria as compared to the median observed NDVI (0.66) at month lag 2-4, with the highest
cumulative IRR of 1.57(95% CI: 1.09-2.25) at lag month 4. The rate of increase in cumulative IRR of
malaria was highest within lag months 1-2 as compared to lag months 3-4 for all the environmental
covariates.
Conclusions In high-malaria transmission settings, high values of environmental covariates were
associated with cumulative increases in the incidence of malaria, with peak associations occurring after
variable lag times. The complex associations identified are valuable for designing strategies for early
warning, prevention, and control of seasonal malaria surges and epidemics.
Description
Keywords
Malaria, Incidence, Associations, Environmental, Covariates, Temporal, DLNM
Citation
Okiring, J., Routledge, I., Esptein, A., Namuganga, J. F., Kamya, E. V., Obeng-Amoako, G. O., ... & Nankabirwa, J. I. (2021). Associations between environmental covariates and malaria incidence in high transmission settings of Uganda: A distributed non-linear lagged ecological analysis. DOI: https://doi.org/10.21203/rs.3.rs-358891/v1