Spatial-temporal analysis of climate and socioeconomic conditions on cholera incidence in Mozambique from 2000 to 2018: an ecological longitudinal retrospective study.


Journal

BMJ open
ISSN: 2044-6055
Titre abrégé: BMJ Open
Pays: England
ID NLM: 101552874

Informations de publication

Date de publication:
19 Aug 2024
Historique:
medline: 20 8 2024
pubmed: 20 8 2024
entrez: 19 8 2024
Statut: epublish

Résumé

This study aims to assess both socioeconomic and climatic factors of cholera morbidity in Mozambique considering both spatial and temporal dimensions. An ecological longitudinal retrospective study using monthly provincial cholera cases from Mozambican Ministry of Health between 2000 and 2018. The cholera cases were linked to socioeconomic data from Mozambique Demographic and Health Surveys conducted in the period 2000-2018 and climatic data; relative humidity (RH), mean temperature, precipitation and Normalised Difference Vegetation Index (NDVI). A negative binomial regression model in a Bayesian framework was used to model cholera incidence while adjusting for the spatiotemporal covariance, lagged effect of environmental factors and the socioeconomic indicators. Eleven provinces in Mozambique. Over the 19-year period, a total of 153 941 cholera cases were notified to the surveillance system in Mozambique. Risk of cholera increased with higher monthly mean temperatures above 24°C in comparison to the reference mean temperature of 23°C. At mean temperature of 19°C, cholera risk was higher at a lag of 5-6 months. At a shorter lag of 1 month, precipitation of 223.3 mm resulted in an 57% increase in cholera risk (relative risk, RR 1.57 (95% CI 1.06 to 2.31)). Cholera risk was greatest at 3 lag months with monthly NDVI of 0.137 (RR 1.220 (95% CI 1.042 to 1.430)), compared with the reference value of 0.2. At an RH of 54%, cholera RR was increased by 62% (RR 1.620 (95% CI 1.124 to 2.342)) at a lag of 4 months. We found that ownership of radio RR 0.29, (95% CI 0.109 to 0.776) and mobile phones RR 0.262 (95% CI 0.097 to 0.711) were significantly associated with low cholera risk. The derived lagged patterns can provide appropriate lead times in a climate-driven cholera early warning system that could contribute to the prevention and management of outbreaks.

Identifiants

pubmed: 39160100
pii: bmjopen-2023-082503
doi: 10.1136/bmjopen-2023-082503
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e082503

Informations de copyright

© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Chaibo Jose Armando (CJ)

Department of Public Health and Clinical Medicine, Sustainable Health Section, Umeå University, Umea, Sweden cjarmando.jose@gmail.com.
Eduardo Mondlane University, Maputo, Mozambique.

Joacim Rocklöv (J)

Department of Public Health and Clinical Medicine, Sustainable Health Section, Umeå University, Umea, Sweden.
Heidelberg Institute of Global Health and Interdisciplinary Centre for Scientific Computing, Heidelberg University, Heidelberg, Germany.

Mohsin Sidat (M)

Eduardo Mondlane University, Maputo, Mozambique.

Yesim Tozan (Y)

School of Global Public Health, NYU, New York, New York, USA.

Alberto Francisco Mavume (AF)

Eduardo Mondlane University, Maputo, Mozambique.

Aditi Bunker (A)

Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.

Maquins Odhiambo Sewe (MO)

Department of Public Health and Clinical Medicine, Sustainable Health Section, Umeå University, Umea, Sweden.
Universitatsklinikum Heidelberg Heidelberg Institute of Global Health, Heidelberg, Germany.

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