Correlation of climate variability and malaria: A retrospective comparative study, Southwest Ethiopia

Sena, Lelisa; Deressa, Wakgari; Ali, Ahmed

doi:10.4314/ejhs.v25i2.5

Cited by 38 publications

(37 citation statements)

References 33 publications

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“…In contrast to our nding, minimum temperature was weakly correlated with malaria cases in southeast Ethiopia [42]. Ideally, rainfall and minimum temperature play a vital role in breeding and survival of malaria vectors and the respective parasites.…”

Section: Discussioncontrasting

confidence: 99%

“…Moreover, average monthly maximum temperature and relative humidity were weakly correlated with malaria cases. In disagreement to our nding, studies conducted in Jimma, Ethiopia by Alemu and others [41] and Sena and colleagues [42] in Gilgel-Gibe, southwest Ethiopia reported that inter-monthly relative humidity was signi cantly associated with monthly malaria cases.…”

Section: Discussioncontrasting

confidence: 99%

“…Monthly rainfall and minimum temperature demonstrated statistically signi cant positive correlation with malaria cases. Previous studies in Ethiopia [41,42] and elsewhere [43,44] documented similar ndings.…”

Section: Discussionsupporting

confidence: 82%

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Eight-year Retrospective Analysis of Malaria Trends in Gedeo Zone, South Ethiopia (2012-2019)

Belete

Behaksra

Tadesse

et al. 2020

Preprint

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Background: Informed decision making is underlined by all level of the tiers in the health system. Poor data record system coupled with under- (over)-reporting of malaria cases affects the country’s elimination activities. Thus, malaria data at health facilities and health offices are important particularly to monitor and evaluate malaria elimination progresses. This study was intended to assess overall reported malaria cases, spatiotemporal trends and factors associated in Gedeo zone, South Ethiopia, and compare malaria case reports by the health centers and health offices.Methods: Past eight years retrospective data stored in 17 health centers and 5 district health offices in Gedeo Zone were extracted. Malaria cases data at each health center with sociodemographic information, between 2012 and 2019, were included. Meteorological data were obtained from the national meteorology agency. The data were analyzed using Stata 13.Results: A total of 485,414 clinical suspects were examined for malaria during the previous 8 years at health centers. Of these suspects, 57,228 (11.79%) were confirmed malaria cases. We noted, an overall under reporting of malaria, 3,758 clinical suspects and 467 confirmed malaria cases were not captured at the health offices level. Based on the health centers records, Plasmodium falciparum (49.74%) was slightly higher (p = 0.795) than P. vivax (47.59%). The majority of cases were found in adults (≥15 years of age) that accounted for 11.47% of confirmed malaria cases (p < 0.0001). There was high spatiotemporal variation: highest cases record was during autumn (12.55%) (p < 0.0001) and, the highest (18,150, 13.17%)) and lowest (5,187 (10.44%)) malaria cases were reported from Dilla town and Yirgacheffe rural district, respectively (p = 0.0002). Monthly rainfall and minimum temperature exhibited strong positive associations with the number of confirmed malaria cases.Conclusion: A notable decline in malaria cases was observed over the eight-year period. Both P. falciparum and P. vivax co-exist; hence, control measures should continue targeting both species. The high malaria burden in urban (Dilla town) and suburban (Dilla zuria district) settings and autumn season need spatiotemporal consideration by the elimination program.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussioncontrasting

confidence: 99%

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Eight-year Retrospective Analysis of Malaria Trends in Gedeo Zone, South Ethiopia (2012-2019)

Belete

Behaksra

Tadesse

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Also, in some of the years, rainfall is negatively correlated with number of malaria cases at lags of 0 and 1 month. This is consistence with the previous study of [34]. However, our result here contradicts their findings that temperature is weakly correlated at lags of 0 to 4 months.…”

Section: The Lag and Cross-correlation Of Climate Variability And Malsupporting

confidence: 75%

Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

Abiodun¹,

Witbooi²,

Okosun³

et al. 2018

TOIDJ

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Introduction: The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas. Methods: In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence. Results: Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

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“…In 2010, 90% of the reported cases in Iran belonged to the southeastern parts of the country (4)(5)(6)(7)(8). In spite of the fact that the climate-malaria connection is not yet completely understood, scientific communities know that there is an important balance of temperature, rainfall, and humidity that creates ideal conditions for mosquitoes to breed and transmit malaria parasites (9)(10)(11)(12)(13).…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variability of Malaria Infection in Chahbahar County, Iran: Association with the ENSO and Rainfall Variability

Nazemosadat¹,

Salehi²,

Ghaedamini³

et al. 2020

Preprint

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Background: Malaria is one of the most widespread communicable diseases in the southeast of Iran particularly in Chahbahar County. Comprehensive understanding of the influence of climate on this disease is a key element for success in the environmental-based malaria elimination programs. After analyzing the spatio-temporal distribution of the disease, the relationships between the infection statistics and some important climate indices particularly the El Niño-Southern Oscillation (ENSO) and rainfall were investigated.Methods: The malaria statistics collected from various health centers were composited with the corresponding data of Southern Oscillation Index (SOI), ground-based meteorological records and satellite-based rainfall data. Non-parametric Mann-whitely test was applied to detect the significant difference between patient number between El Niño and La Niña and between the adopted wet and dry episodes.Findings: Patient number from highest to lowest was associated to summer, autumn, spring and winter, respectively. Plasmodium falciparum, Plasmodium vivax and other species were responsible for 22%, 75% and 3% of the sickness, respectively. While the outbreak of P. falciparum is in autumn; P. vivax is erupted in summer. When the epidemic statistics were collected from rural rather than urban areas, the effect of climate on the infection statistic was more obvious.Interpretation: For rural / urban areas, the infection statistics exhibited a significant decline / increase during El Niño episodes. In autumn, spring and winter, patient number has significantly increased / decreased during the dry / wet epochs, respectively. These relationships were, however, reversed during summertime of health indicators are rarely available for every population and period of interest, and available data.Funding: Shiraz University of Medical Sciences

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Correlation of climate variability and malaria: A retrospective comparative study, Southwest Ethiopia

Cited by 38 publications

References 33 publications

Eight-year Retrospective Analysis of Malaria Trends in Gedeo Zone, South Ethiopia (2012-2019)

Eight-year Retrospective Analysis of Malaria Trends in Gedeo Zone, South Ethiopia (2012-2019)

Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

Spatio-Temporal Variability of Malaria Infection in Chahbahar County, Iran: Association with the ENSO and Rainfall Variability

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