Investment case for malaria elimination in South Africa: a financing model for resource mobilization to accelerate regional malaria elimination

Abstract

Background Malaria continues to be a public health problem in South Africa. While the disease is mainly confined to three of the nine provinces, most local transmissions occur because of importation of cases from neighbouring countries. The government of South Africa has reiterated its commitment to eliminate malaria within its borders. To support the achievement of this goal, this study presents a cost–benefit analysis of malaria elimination in South Africa through simulating different scenarios aimed at achieving malaria elimination within a 10-year period. Methods A dynamic mathematical transmission model was developed to estimate the costs and benefits of malaria elimination in South Africa between 2018 and 2030. The model simulated a range of malaria interventions and estimated their impact on the transmission of Plasmodium falciparum malaria between 2018 and 2030 in the three endemic provinces of Limpopo, Mpumalanga and KwaZulu-Natal. Local financial, economic, and epidemiological data were used to calibrate the transmission model. Results Based on the three primary simulated scenarios: Business as Usual, Accelerate and Source Reduction, the total economic burden was estimated as follows: for the Business as Usual scenario, the total economic burden of malaria in South Africa was R 3.69 billion (USD 223.3 million) over an 11-year period (2018–2029). The economic burden of malaria was estimated at R4.88 billion (USD 295.5 million) and R6.34 billion (~ USD 384 million) for the Accelerate and Source Reduction scenarios, respectively. Costs and benefits are presented in midyear 2020 values. Malaria elimination was predicted to occur in all three provinces if the Source Reduction strategy was adopted to help reduce malaria rates in southern Mozambique. This could be achieved by limiting annual local incidence in South Africa to less than 1 indigenous case with a prediction of this goal being achieved by the year 2026. Conclusions Malaria elimination in South Africa is feasible and economically worthwhile with a guaranteed positive return on investment (ROI). Findings of this study show that through securing funding for the proposed malaria interventions in the endemic areas of South Africa and neighbouring Mozambique, national elimination could be within reach in an 8-year period.

Predicting malaria outbreaks from sea surface temperature variability up to 9 months ahead in Limpopo, South Africa, using machine learning

“…Atmospheric variables (surface temperature and precipitation), that are expected to have a direct impact on the life cycles of the Anopheles mosquito and Plasmodium falciparum parasite , and other variables indicative of the passage of weather systems (surface pressure and surface wind) affecting those atmospheric variables are analyzed over Limpopo. Since temperature and precipitation over Mozambique were also shown to be associated with malaria outbreaks in Limpopo ( 52 ), likely through importation of cases originating from Mozambique via cross-border human migration ( 75 ), we also consider their variability here. Among the important precursors, there is an overall tendency for precipitation to be enhanced over a period of 12 months leading to malaria outbreaks in the early malaria season (Sep-Dec) of Limpopo and Mozambique.…”

“…One limitation of the prediction method developed herein is the exclusion of socioeconomic factors, which also influence infection rates ( 73 , 74 ). For instance, cross-border migration can contribute to up to 70% of observed cases in South Africa ( 75 ), thus year-to-year changes in migration may influence malaria infection rates. It cannot however be included in the machine-learning techniques developed herein because it is not adequately monitored ( 75 , 76 ).…”

“…For instance, cross-border migration can contribute to up to 70% of observed cases in South Africa ( 75 ), thus year-to-year changes in migration may influence malaria infection rates. It cannot however be included in the machine-learning techniques developed herein because it is not adequately monitored ( 75 , 76 ). The sharing of malaria case data together with human migration data among South African counties would be helpful to further improve such early warning systems of malaria.…”

Efficacy of Plasmoquine for the Treatment of Plasmodium Vivax and Plasmodium Falciparum

“…Since 2010, South Africa has made significant progress in combating malaria within its borders. However, South Africa has experienced at least two major malaria outbreaks in the last two decades, resulting in hundreds of hospital admissions and deaths [12]. The first outbreak, which was primarily concentrated in the province of KwaZulu-Natal, occurred in early 2000, with over 60,000 cases recorded [12].…”

“…However, South Africa has experienced at least two major malaria outbreaks in the last two decades, resulting in hundreds of hospital admissions and deaths [12]. The first outbreak, which was primarily concentrated in the province of KwaZulu-Natal, occurred in early 2000, with over 60,000 cases recorded [12]. The most recent malaria outbreak was reported in South Africa in 2017, with over 28,000 cases recorded, with Limpopo province accounting for the majority of new malaria transmissions [13].…”