Spatio-temporal dynamics of malaria expansion under climate change in semi-arid areas of Ethiopia

Abrha, Haftu; Hagos, Haftom; Brhane, Emiru; Hadgu, Meseret; Mamo, Girma

doi:10.1080/17477891.2019.1609405

Cited by 8 publications

(7 citation statements)

References 51 publications

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“…On top of this, temperature suitability for malaria is climbing into the highlands of Ethiopia (42, 43) because of which the prevalence of malaria is projected to increase (44). A case study in northern Ethiopia shows that climate change may increase area suitable for malaria transmission by 94 to 114% by 2050 (45). Overall, countrywide, up to 130 million people may be at risk of malaria by 2070 (46) that could induce substantial economic costs (8,42).…”

Section: Emerging Challengesmentioning

confidence: 99%

Achievements, Gaps, and Emerging Challenges in Controlling Malaria in Ethiopia

Yalew

2022

Front. Trop. Dis

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Controlling malaria is one of the top health sector priorities in Ethiopia. The concrete prevention, control, and treatment interventions undertaken in the past two decades have substantially reduced the morbidity and mortality attributable to malaria. Emboldened by these past achievements, Ethiopia envisages to eliminate malaria by 2030. Realizing this ambition, however, needs to further strengthen the financial, technical, and institutional capacities to address the current as well as emerging challenges. It particularly needs to step up measures pertaining to diagnosis, domestic resource mobilization, vector surveillance, and seasonal weather forecasting.

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Section: Emerging Challengesmentioning

confidence: 99%

Achievements, Gaps, and Emerging Challenges in Controlling Malaria in Ethiopia

Yalew

2022

Front. Trop. Dis

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“…The prevalence of malaria will increase in all regions (Taye et al, 2015) as temperature suitability for malaria is climbing into the highlands of Ethiopia (Lyon et al, 2017). Moreover, in three selected districts in northern Ethiopia, the area suitable for malaria transmission is projected to increase by 93.8% to 113.9% and 149% to 161% by mid and end of the century, respectively (Abrha et al, 2019).…”

Section: Climate Change and Its Implication For Malariamentioning

confidence: 99%

“…There are already a few studies addressing this issue. One can refer to research outputs from previous and ongoing projects such as the Ethiopian Malaria Prediction System by the University of Bergen and partners (Lindtjørn et al, 2014), the Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment by South Dakota State University and partners (Merkord et al, 2017), the Enhanced National Climate Services by the International Research Institute for Climate and Society and partners (Lyon et al, 2017), the vector-borne diseases impact modeling consortium in the Inter-Sectoral Impact Model Intercomparison Project (Caminade et al, 2014) and many other studies (Abrha et al, 2019;Ermert et al, 2013Ermert et al, , 2012Tanser et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

“…The existing literature on the impacts of climate change in Ethiopia, however, barely touches the impacts on health in general and on malaria in particular (Taye et al, 2015). There are exceptions (Abrha et al, 2019;Lyon et al, 2017) which focus on the effects of climate change on the transmission and prevalence of malaria but hardly discussed the ensuing socio-economic impacts. As the subject is inherently inter-disciplinary, one of the reasons for this gap may attribute to the lack of a conceptual framework to assess the economic effects of the malaria disease burden with and without climate change.…”

Section: Introductionmentioning

confidence: 99%

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Revisiting economic burdens of malaria in the face of climate change: a conceptual analysis for Ethiopia

Yalew

2020

IJCCSM

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Purpose Climate change affects the geographic and seasonal range of malaria incidence, especially, in poor tropical countries. This paper aims to attempt to conceptualize the potential economic repercussions of such effects with its focus on Ethiopia. Design/methodology/approach The paper is conceptual and descriptive in its design. It first reviews existing literature and evidence on the economic burdens of malaria, and the impacts of climate change on malaria disease. It then draws the economic implications of the expected malaria risk under the future climate. This is accompanied by a discussion on a set of methods that can be used to quantify the economic effects of malaria with or without climate change. Findings A review of available evidence shows that climate change is likely to increase the geographic and seasonal range of malaria incidence in Ethiopia. The economic consequences of even a marginal increase in malaria risk will be substantial as one considers the projected impacts of climate change through other channels, the current population exposed to malaria risk and the country’s health system, economic structure and level of investment. The potential effects have the potency to require more household and public spending for health, to perpetuate poverty and inequality and to strain agricultural and regional development. Originality/value This paper sheds light on the economic implications of climate change impacts on malaria, particularly, in Agrarian countries laying in the tropics. It illustrates how such impacts will interact with other impact channels of climate change, and thus evolve to influence the macro-economy. The paper also proposes a set of methods that can be used to quantify the potential economic effects of malaria. The paper seeks to stimulate future research on this important topic which rather has been neglected.

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“…Studies where the maximum entropy tool was used to determine the spatial distribution of the local Anopheles mosquito species have been undertaken in regions all over the world, including Asia and the Middle East [ 9 ], South America [ 10 , 11 ], and Africa [ 12 , 13 ]. MaxEnt has also been used to model the effects of climate change on malaria transmission and Anopheles species density in China [ 14 ], Iran [ 15 ], and parts of Africa [ 16 ]. In the model, local P. vivax malaria cases were used to train the machine learning model and estimate the percent probability of malaria occurrence given certain geographical and population factors.…”

Section: Introductionmentioning

confidence: 99%

Understanding work-related travel and its relation to malaria occurrence in Thailand using geospatial maximum entropy modelling

Memarsadeghi

Stewart

et al. 2023

Malar J

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Background Estimating malaria risk associated with work locations and travel across a region provides local health officials with information useful to mitigate possible transmission paths of malaria as well as understand the risk of exposure for local populations. This study investigates malaria exposure risk by analysing the spatial pattern of malaria cases (primarily Plasmodium vivax) in Ubon Ratchathani and Sisaket provinces of Thailand, using an ecological niche model and machine learning to estimate the species distribution of P. vivax malaria and compare the resulting niche areas with occupation type, work locations, and work-related travel routes. Methods A maximum entropy model was trained to estimate the distribution of P. vivax malaria for a period between January 2019 and April 2020, capturing estimated malaria occurrence for these provinces. A random simulation workflow was developed to make region-based case data usable for the machine learning approach. This workflow was used to generate a probability surface for the ecological niche regions. The resulting niche regions were analysed by occupation type, home and work locations, and work-related travel routes to determine the relationship between these variables and malaria occurrence. A one-way analysis of variance (ANOVA) test was used to understand the relationship between predicted malaria occurrence and occupation type. Results The MaxEnt (full name) model indicated a higher occurrence of P. vivax malaria in forested areas especially along the Thailand–Cambodia border. The ANOVA results showed a statistically significant difference between average malaria risk values predicted from the ecological niche model for rubber plantation workers and farmers, the two main occupation groups in the study. The rubber plantation workers were found to be at higher risk of exposure to malaria than farmers in Ubon Ratchathani and Sisaket provinces of Thailand. Conclusion The results from this study point to occupation-related factors such as work location and the routes travelled to work, being risk factors in malaria occurrence and possible contributors to transmission among local populations.

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Spatio-temporal dynamics of malaria expansion under climate change in semi-arid areas of Ethiopia

Cited by 8 publications

References 51 publications

Achievements, Gaps, and Emerging Challenges in Controlling Malaria in Ethiopia

Achievements, Gaps, and Emerging Challenges in Controlling Malaria in Ethiopia

Revisiting economic burdens of malaria in the face of climate change: a conceptual analysis for Ethiopia

Understanding work-related travel and its relation to malaria occurrence in Thailand using geospatial maximum entropy modelling

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