Synergies between environmental degradation and climate variation on malaria re-emergence in southern Venezuela: a spatiotemporal modelling study

Fletcher, Isabel; Grillet, María Eugenia; Moreno, José A.; Drakeley, Chris; Hernández-Villena, Juan V; Jones, Kate; Lowe, Rachel

doi:10.1016/s2542-5196(22)00192-9

Cited by 17 publications

(8 citation statements)

References 44 publications

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“…Of particular interest in this study is quantification of geographical differences in under-five malaria risk continuously over the whole of Ghana as indicated in the predicted spatial maps. The 5 × 5 km high resolution predictive maps showed substantial geographical differences in the predicted malaria prevalence and identified specific communities/towns with highest concentration of malaria risk, supporting previous studies that observed that health outcomes like malaria, malnutrition, mortality and other related health outcomes exhibit spatial patterns and that the identification of these geographical patterns are of outmost importance urgent and targeted public health policy and intervention, especially in prevention and control efforts with the goal of improving health outcomes in populations at sub-national, national and global levels [6,7,20,35,[37][38][39]. The overall predicted national malaria prevalence is 16.3% (SE = 8.9%), characterized by substantial localized geographical differences with the highest observed in parts of Central and Bono East regions (41.3-51.4%) and lowest in parts of Greater Accra, Eastern, Northern, Volta, Upper West, Savannah, and Ashanti regions (0.665-10.9%).…”

Section: Discussionsupporting

confidence: 84%

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web-based mapping methods

Aheto

2022

Malar J

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Background Under-five child malaria is one of the leading causes of morbidity and mortality globally, especially among sub-Saharan African countries like Ghana. In Ghana, malaria is responsible for about 20,000 deaths in children annually of which 25% are those aged < 5 years. To provide opportunities for efficient malaria surveillance and targeted control efforts amidst limited public health resources, the study produced high resolution interactive web-based spatial maps that characterized geographical differences in malaria risk and identified high burden communities. Methods This modelling and web-based mapping study utilized data from the 2019 Malaria Indicators Survey (MIS) of the Demographic and Health Survey Program. A novel and advanced Bayesian geospatial modelling and mapping approaches were utilized to examine predictors and geographical differences in under-five malaria. The model was validated via a cross-validation approach. The study produced an interactive web-based visualization map of the malaria risk by mapping the predicted malaria prevalence at both sampled and unsampled locations. Results In 2019, 718 (25%) of 2867 under-five children surveyed had malaria. Substantial geographical differences in under-five malaria risk were observed. ITN coverage (log-odds 4.5643, 95% credible interval = 2.4086–6.8874), travel time (log-odds 0.0057, 95% credible interval = 0.0017–0.0099) and aridity (log-odds = 0.0600, credible interval = 0.0079–0.1167) were predictive of under-five malaria in the spatial model. The overall predicted national malaria prevalence was 16.3% (standard error (SE) 8.9%) with a range of 0.7% to 51.4% in the spatial model with covariates and prevalence of 28.0% (SE 13.9%) with a range of 2.4 to 67.2% in the spatial model without covariates. Residing in parts of Central and Bono East regions was associated with the highest risk of under-five malaria after adjusting for the selected covariates. Conclusion The high-resolution interactive web-based predictive maps can be used as an effective tool in the identification of communities that require urgent and targeted interventions by programme managers and implementers. This is key as part of an overall strategy in reducing the under-five malaria burden and its associated morbidity and mortality in a country with limited public health resources where universal intervention is practically impossible.

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Section: Discussionsupporting

confidence: 84%

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web-based mapping methods

Aheto

2022

Malar J

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“…The short-term impacts of a flood on infant mortality could be interpreted by several pathways. According to previous studies, relative shorter-term high-temperature exposure (1–3 months) may be linked with infectious diseases that mainly contribute to infective anemia, 41 whereas longer-term exposure (e.g., annual temperature) may be linked with water resource, agricultural productivity, and malnutrition and, consequently, cause nutritional anemia. 42 …”

Section: Discussionmentioning

confidence: 99%

Global warming may significantly increase childhood anemia burden in sub-Saharan Africa

Zhu,

He,

Gasparrini

et al. 2023

One Earth

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“…The 5km × 5km high resolution predictive maps showed substantial geographical differences in the predicted malaria prevalence and identified specific communities/towns with highest concentration of malaria risk, supporting previous studies that observed that health outcomes like malaria, malnutrition, mortality and other related health outcomes exhibit spatial patterns and that the identification of these geographical patterns are of outmost importance urgent and targeted public health policy and intervention, especially in prevention and control efforts with the goal of improving health outcomes in populations at sub-national, national and global levels. [6,7,20,35,[37][38][39] The overall predicted national malaria prevalence is 16.3% (SE=8.9%), characterized by substantial localised geographical differences with the highest observed in parts of Central and Bono East regions (41.3-51.4%) and lowest in parts of Greater Accra, Eastern, Northern, Volta, Upper West, Savannah, and Ashanti regions (0.665-10.9%). The findings provide critical information to malaria control programme managers and other stakeholders in public health for urgent and targeted malaria preventive and control efforts where universal intervention is practically impossible amidst limited public health resources.…”

Section: Discussionmentioning

confidence: 99%

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web- based mapping methods

Aheto

2022

Preprint

View full text Add to dashboard Cite

Background: Under-five child malaria is one of the leading causes of morbidity and mortality globally, especially among sub-Saharan African countries like Ghana. In Ghana, malaria is responsible for about 20000 deaths in children annually of which 25% are those aged <5 years. To provide opportunities for efficient malaria surveillance and targeted control efforts amidst limited public health resources, we produced high resolution interactive web-based spatial maps that characterized geographical differences in malaria risk and identified high burden communities. Methods: This modelling and web-based mapping studyutilised data from the 2019 Malaria Indicators Survey (MIS) of the Demographic and Health Survey Program. A novel and advanced Bayesian geospatial modelling and mapping approaches were utilized to examine predictors and geographical differences in under-five malaria. The model was validated via a cross-validation approach. We produced an interactive web-based visualization map of the malaria risk by mapping the predicted malaria prevalence at both sampled and unsampled locations. Results: In 2019, 718 (25%) of 2867 under-five children surveyed had malaria. Substantial geographical differences in under-five malaria risk were observed. ITN coverage (log-odds 4.5643, 95% credible interval = 2.4086 - 6.8874), travel time (log-odds 0.0057, 95% credible interval = 0.0017 - 0.0099) and aridity (log-odds = 0.0600, credible interval = 0.0079 - 0.1167) were predictive of under-five malaria in the spatial model. The overall predicted national malaria prevalence was 16.3% (standard error (SE) 8.9%) with a range of 0.7 % to 51.4% in the spatial model with covariates and prevalence of 28.0% (SE 13.9%) with a range of 2.4 to 67.2% in the spatial model without covariates. Residing in parts of Central and Bono East regions was associated with the highest risk of under-five malaria after adjusting for the selected covariates. Conclusion: The high-resolution interactive web-based predictive maps can be used as an effective tool in the identification of communities that require urgent and targeted interventions by program managers and implementers. This is key as part of an overall strategy in reducing the under-five malaria burden and its associated morbidity and mortality in a country with limited public health resources where universal intervention is practically impossible.

show abstract

Synergies between environmental degradation and climate variation on malaria re-emergence in southern Venezuela: a spatiotemporal modelling study

Cited by 17 publications

References 44 publications

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web-based mapping methods

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web-based mapping methods

Global warming may significantly increase childhood anemia burden in sub-Saharan Africa

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web- based mapping methods

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