Spatiotemporal analysis of climate variability impacts on malaria prevalence in Ghana

Adu-Prah, Samuel; Tetteh, Emmanuel Kofi

doi:10.1016/j.apgeog.2014.10.010

Cited by 19 publications

(10 citation statements)

References 30 publications

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“…In Botswana, it is found that there is a positive correlation between annual malaria anomalies and December to February rainfall [29] . Our results are somewhat in line with those found in many African countries [ 32 , 37 ].…”

Section: Discussionsupporting

confidence: 93%

Malaria's association with climatic variables and an epidemic early warning system using historical data from Gezira State, Sudan

Hussien

2019

Heliyon

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Malaria is a major public health problem in Sudan. Climatic variability is the main risk factor for seasonal and secular patterns of P. falciparum malaria transmission in Gezira state. The purposes of this study is to (1) develop thresholds for action in a malaria epidemic early warning system using three traditional statistical methods including the mean number of malaria cases + 2 standard deviations (SD), percentiles over the median (medium + upper third quartile), and the cumulative sum over prior 10 years (C-SUM) and (2) explore to what extent the climate variability affects malaria transmission. Pearson's correlation coefficient for malaria incidence and rainfall, maximum temperature, relative humidity, and the Blue Nile River level was statistically significant (p < 0.05). However, there was an insignificant correlation between the number of malaria cases and the minimum temperature. Furthermore, the number of cases in 2015 was significantly higher than expected. An evaluation and comparison of the statistical methods for the early detection of malaria showed that there was a considerable variation in the number of cases exceeding an epidemic alert threshold.

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Section: Discussionsupporting

confidence: 93%

Malaria's association with climatic variables and an epidemic early warning system using historical data from Gezira State, Sudan

Hussien

2019

Heliyon

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“…However, minimum and maximum temperature are better predictors. Other studies include that of Adu-Prah and Tetteh [ 12 ] who discovered that temperature and relative humidity both have influence on malaria. However, the effect of rainfall was found to be less significant.…”

Section: Discussionmentioning

confidence: 99%

“…Adu-Prah and Tetteh [ 12 ] are of the opinion that generating relevant information on the role of temperature, rainfall, and humidity on malaria prevalence at different geographic scales is critical to efforts to combat the burden of prevalence. For effective climate change adaptation strategies which involves planning and the necessary implementation of disease control interventions appropriately, a better understanding of the relationship between climatic variables and malaria is needed.…”

Section: Introductionmentioning

confidence: 99%

Modelling Trends of Climatic Variability and Malaria in Ghana Using Vector Autoregression

Ankamah

Nokoe

Abdul

2018

Malaria Research and Treatment

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Malaria is considered endemic in over hundred countries across the globe. Many cases of malaria and deaths due to malaria occur in Sub-Saharan Africa. The disease is of great public health concern since it affects people of all age groups more especially pregnant women and children because of their vulnerability. This study sought to use vector autoregression (VAR) models to model the impact of climatic variability on malaria. Monthly climatic data (rainfall, maximum temperature, and relative humidity) from 2010 to 2015 were obtained from the Ghana Meteorological Agency while data on malaria for the same period were obtained from the Ghana Health Service. Results of the Granger and instantaneous causality tests led to a conclusion that malaria is influenced by all three climatic variables. The impulse response analyses indicated that the highest positive effect of maximum temperature, relative humidity, and rainfall on malaria is observed in the months of September, March, and October, respectively. The decomposition of forecast variance indicates varying degree of malaria dependence on the climatic variables, with as high as 12.65% of the variability in the trend of malaria which has been explained by past innovations in maximum temperature alone. This is quite significant and therefore, policy-makers should not ignore temperature when formulating policies to address malaria.

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“…Although the impacts of climate change on infectious diseases are detected worldwide, the forms and degree of impacts differ greatly. Because of the complex interactions process between climate variables and infectious diseases’ components (pathogen, host and transmission environment) for the specific diseases [ 4 ], the impacts are different at different geographic scales for different infectious diseases, and sometimes controversial [ 46 , 47 ]. Moreover, the incidence of infectious disease is tied to many other factors besides climate, such as the location of the respective countries and socio-economical situations, pollution, and healthcare conditions [ 46 ].…”

Section: Applicationmentioning

confidence: 99%

A Method for Screening Climate Change-Sensitive Infectious Diseases

Wang

Rao

et al. 2015

IJERPH

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Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change.

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Spatiotemporal analysis of climate variability impacts on malaria prevalence in Ghana

Cited by 19 publications

References 30 publications

Malaria's association with climatic variables and an epidemic early warning system using historical data from Gezira State, Sudan

Malaria's association with climatic variables and an epidemic early warning system using historical data from Gezira State, Sudan

Modelling Trends of Climatic Variability and Malaria in Ghana Using Vector Autoregression

A Method for Screening Climate Change-Sensitive Infectious Diseases

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