Seasonally lagged effects of climatic factors on malaria incidence in South Africa

Ikeda, Takayoshi; Behera, Swadhin K.; Morioka, Yushi; Minakawa, Noboru; Hashizume, Masahiro; Tsuzuki, Ataru; Maharaj, Rajendra; Kruger, Philip

doi:10.1038/s41598-017-02680-6

Cited by 57 publications

(56 citation statements)

References 44 publications

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“…Similar increase in cases were recorded across other epidemic provinces in South Africa during this period [41,5]. Although studies show that most of the cases were imported [27]. For this reason, several malaria control measures were introduced to the provinces, which is traceable to the reduction in transmission after 2002 [41,5].…”

Section: Numerical Results and Discussionsupporting

confidence: 70%

A malaria transmission model with seasonal mosquito life-history traits

Djidjou‐Demasse

Abiodun

Adeola

et al. 2018

Preprint

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In this paper we develop and analyse a malaria model with seasonality of mosquito life-history traits: periodic-mosquitoes per capita birth rate, -mosquitoes death rate, -probability of mosquito to human disease transmission, -probability of human to mosquito disease transmission and -mosquitoes biting rate. All these parameters are assumed to be time dependent leading to a nonautonomous differential equation systems. We provide a global analysis of the model depending on two thresholds parameters R0 and R0 < 1 (with R0 ≤ R0). When R0 < 1, then the disease-free stationary state is locally asymptotically stable. In the presence of the human disease-induced mortality, the global stability of the disease-free stationary state is guarantied when R0 < 1. On the contrary, if R0 > 1, the disease persists in the host population in the long term and the model admits at least one positive periodic solution. Moreover, by a numerical simulation, we show that a subcritical (backward) bifurcation is possible at R0 = 1. Finally, the simulation results are in accordance with the seasonal variation of the reported cases of a malaria-epidemic region in Mpumalanga province in South Africa.

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Section: Numerical Results and Discussionsupporting

confidence: 70%

A malaria transmission model with seasonal mosquito life-history traits

Djidjou‐Demasse

Abiodun

Adeola

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Similar increases in cases were recorded across other epidemic provinces in South Africa during this period . Although studies show that most of the cases were imported . For this reason, several malaria control measures were introduced to the provinces, which is traceable to the reduction in transmission after 2002 …”

Section: Numerical Results and Discussionsupporting

confidence: 69%

“…Although generally a significant proportion of malaria cases over South Africa are imported, the current study focuses on locally transmitted cases with a closed system of exposed or infected population. It is envisaged that incorporating the impact of migration (into exposed and/or infectious human compartments) the model could yield more precise results.…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

Development and analysis of a malaria transmission mathematical model with seasonal mosquito life‐history traits

et al. 2019

View full text Add to dashboard Cite

In this paper, we develop and analyze a malaria model with seasonality of mosquito life-history traits: periodicmosquitoes per capita birth rate, -mosquitoes death rate, -probability of mosquito to human disease transmission, -probability of human to mosquito disease transmission, and -mosquitoes biting rate. All these parameters are assumed to be time dependent leading to a nonautonomous differential equation system. We provide a global analysis of the model depending on two threshold parameters  0 and  0 < 1 (with  0 ≤  0 ). When  0 < 1, then the disease-free stationary state is locally asymptotically stable. In the presence of the human disease-induced mortality, the global stability of the disease-free stationary state is guarantied when  0 < 1. On the contrary, if  0 > 1, the disease persists in the host population in the long term and the model admits at least one positive periodic solution.Moreover, by a numerical simulation, we show that a sub-critical (backward) bifurcation is possible at  0 = 1. Finally, the simulation results are in accordance with the seasonal variation of the reported cases of a malariaepidemic region in Mpumalanga province in South Africa. K E Y W O R D S basic reproduction number, global stability, periodic solution, seasonal pattern, uniform persistence Stud Appl Math. 2020;144:389-411.wileyonlinelibrary.com/journal/sapm

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“…These results enable us to pinpoint regions where interventions need to be revisited to consider how climate will alter risk profiles in the future. The strong seasonal cycle of malaria across Southern Africa is related to climate and weather conditions [25,26]. Thus, during some periods of the year, climate conditions are not conducive to spread of the disease.…”

Section: Discussionmentioning

confidence: 99%

Shifting transmission risk for malaria in Africa with climate change: a framework for planning and intervention

Ryan

Lippi

Zermoglio³

2019

Preprint

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AbstractBackgroundMalaria continues to be a disease of massive burden in Africa, and the public health resources targeted at surveillance, prevention, control, and intervention comprise large outlays of expense. Malaria transmission is largely constrained by the suitability of the climate for Anopheles mosquitoes and Plasmodium parasite development. Thus, as climate changes, we will see shifts in geographic locations suitable for transmission, and differing lengths of seasons of suitability, which will require changes in the types and amounts of resources.MethodsWe mapped the shifting geographic risk of malaria transmission, in context of changing seasonality (i.e. endemic to epidemic, and vice-versa), and the number of people affected. We applied a temperature-dependent model of malaria transmission suitability to continental gridded climate data for multiple future climate model projections. We aligned the resulting outcomes with programmatic needs to provide summaries at national and regional scales for the African continent. Model outcomes were combined with population projections to estimate the population at risk at three points in the future, 2030, 2050, and 2080, under two scenarios of greenhouse gas emissions (RCP4.5 and RCP8.5).ResultsGeographic shifts in endemic and seasonal suitability for malaria transmission were observed across all future scenarios of climate change. The worst-case regional scenario (RCP8.5) of climate change places an additional 75.9 million people at risk from endemic (10-12 months) exposure to malaria transmission in Eastern and Southern Africa by the year 2080, with the greatest population at risk in Eastern Africa. Despite a predominance of reduction in season length, a net gain of 51.3 million additional people will be put at some level of risk in Western Africa by midcentury.ConclusionsThis study provides an updated view of potential malaria geographic shifts in Africa under climate change for the more recent climate model projections (AR5), and a tool for aligning findings with programmatic needs at key scales for decision makers. In describing shifting seasonality, we can capture transitions between endemic and epidemic risk areas, to facilitate the planning for interventions aimed at year-round risk versus anticipatory surveillance and rapid response to potential outbreak locations.

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Seasonally lagged effects of climatic factors on malaria incidence in South Africa

Cited by 57 publications

References 44 publications

A malaria transmission model with seasonal mosquito life-history traits

A malaria transmission model with seasonal mosquito life-history traits

Development and analysis of a malaria transmission mathematical model with seasonal mosquito life‐history traits

Shifting transmission risk for malaria in Africa with climate change: a framework for planning and intervention

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