Assessing the Impact of Climatic Variables on Malaria Cases among Pregnant Women in South-Western Nigeria

Sadiq, Babajide; Brown, Perry

doi:10.13189/ujph.2017.050707

Cited by 2 publications

(3 citation statements)

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“…This happens to correlate with the findings in this study, namely that temperature lead malaria incidence by two months. Similarly, our findings also correlates with a study from Ogun State (25) that investigated how climatic factors affected malaria cases in pregnant women and found a link between maximum temperature, humidity, and rainfall with malaria cases. Likewise, our chosen SARIMA model correlates with a model in the study area (25).…”

Section: Discussionsupporting

confidence: 90%

“…Similarly, our findings also correlates with a study from Ogun State (25) that investigated how climatic factors affected malaria cases in pregnant women and found a link between maximum temperature, humidity, and rainfall with malaria cases. Likewise, our chosen SARIMA model correlates with a model in the study area (25). Findings from a study by Omogunloye et al (17) also show that maximum temperatures were statistically significant with malaria prevalence in different local government areas in Lagos State, which correlate with findings in this study.…”

Section: Discussionsupporting

confidence: 90%

“…Similarly, our findings also correlates with a study from Ogun State (25) that investigated how climatic factors affected malaria cases in pregnant women and found a link between maximum temperature, humidity, and rainfall with malaria cases. Likewise, our chosen SARIMA model correlates with a model in the study area (25). While previous studies have assessed the relationship between rainfall and malaria cases within specific localities and communities, employing survey and hospital data (28,29), the present findings using data from the DHIS2 presents a distinct contribution, offering valuable insights.…”

Section: Discussionmentioning

confidence: 80%

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Investigating the relationship between climatic factors and malaria transmission dynamics in Southwest states of Nigeria

Yusuf,

Okoronkwo,

Ademu

et al. 2024

Preprint

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Background In order to combat malaria, numerous strategic initiatives have been deployed over the years, with the goal of eliminating the disease in Nigeria. Despite these efforts, malaria morbidity still persists across the nation, and is presently under control measures. Various factors, encompassing both climatic and non-climatic elements, significantly impact the dynamics of malaria transmission across the country. This study applied time series analysis methods to understand the relationship between climatic factors, particularly temperature and rainfall, and the occurrence of malaria in the Southwest area of Nigeria. Methods This study analysed monthly data on documented cases of uncomplicated malaria obtained from the District Health Information System version 2, overseen by the Federal Ministry of Health. Additionally, monthly rainfall and temperature data spanning from 2013 to 2021, acquired from the Nigeria Meteorological Agency, were analysed. The datasets used for analysis were accessed on June 7, 2022, for research purposes. We applied univariate time series models to analyse monthly data on average temperature, rainfall, and malaria cases. Subsequently, cross-correlation analyses were conducted to investigate the relationships between malaria case data and the corresponding rainfall and temperature patterns, following a pre-whitening process. Results The patterns of malaria transmission exhibit variability among the various states within the Southwest region of Nigeria from 2013 to 2021. On average, Oyo State consistently recorded relatively higher temperatures compared to its neighbouring states. Conversely, Ondo State receives a higher average monthly rainfall. This state, similar to others in the region, experiences two distinct wet seasons, each characterised by different peak periods. In terms of temporal relationships, it is predicted that rainfall precedes malaria cases by one month across all the states. However, with regard to temperature, the five other states (excluding Osun state) lead by two months. Conclusion The results of this study underscore the varied characteristics of malaria transmission patterns and climate change, even across the individual states within the Southwest region of the country. This recognition of variations in malaria transmission and climatic factors is valuable for policymakers as it enables them to strategically allocate and optimise the implementation of interventions at state-specific level, rather than at zonal level. These interventions might involve distributing and advocating for the use of insecticide-treated bed nets, indoor residual spraying, and seasonal malaria chemoprevention tailored to the unique requirements and circumstances at the state level.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 90%

“…Similarly, our findings also correlates with a study from Ogun State (25) that investigated how climatic factors affected malaria cases in pregnant women and found a link between maximum temperature, humidity, and rainfall with malaria cases. Likewise, our chosen SARIMA model correlates with a model in the study area (25). While previous studies have assessed the relationship between rainfall and malaria cases within specific localities and communities, employing survey and hospital data (28,29), the present findings using data from the DHIS2 presents a distinct contribution, offering valuable insights.…”

Section: Discussionmentioning

confidence: 80%

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