Reducing malaria transmission with reactive focal interventions

Quantifying the impact of interventions against Plasmodium vivax: A model for country-specific use

In order to evaluate the impact of various intervention strategies on Plasmodium vivax dynamics in low endemicity settings without significant seasonal pattern, we introduce a simple mathematical model that can be easily adapted to reported case numbers similar to that collected by surveillance systems in various countries. The model includes case management, vector control, mass drug administration and reactive case detection interventions and is implemented in both deterministic and stochastic frameworks. It is available as an R package to enable users to calibrate and simulate it with their own data. Although we only illustrate its use on fictitious data, by simulating and comparing the impact of various intervention combinations on malaria risk and burden, this model could be a useful tool for strategic planning, implementation and resource mobilization.

A Systematic Review and Meta-Analysis of Malaria Test Positivity Outcomes and Programme Interventions in Low Transmission Settings in Southern Africa, 2000-2021

Malaria is one of the most significant causes of mortality and morbidity globally, especially in sub-Saharan Africa (SSA) countries. It harmfully disturbs the public’s health and the economic growth of many developing countries. Despite the massive effect of malaria transmission, the overall pooled proportion of malaria positivity rate in Southern Africa is still elusive. Therefore, the objective of this systematic review and meta-analysis is to pool estimates of the incidence of the malaria positivity rate, which is the first of its kind in South African countries. A literature search is performed to identify all published articles reporting the incidence of malaria positivity in Southern Africa. Out of the 3359 articles identified, 17 studies meet the inclusion for systematic review and meta-analysis. In addition, because substantial heterogeneity is expected due to the studies being extracted from the universal population, random-effects meta-analyses are carried out to pool the incidence of the malaria positivity rate from diverse diagnostic methods. The result reveals that between-study variability is high (τ2 = 0.003; heterogeneity I2 = 99.91% with heterogeneity chi-square χ2 = 18,143.95, degree of freedom = 16 and a p-value < 0.0001) with the overall random pooled incidence of 10% (95%CI: 8−13%, I2 = 99.91%) in the malaria positivity rate. According to the diagnostic method called pooled incidence estimate, the rapid diagnostic test (RDT) is the leading diagnostic method (17%, 95%CI: 11−24%, I2 = 99.95%), followed by RDT and qPCR and RDT and loop mediated isothermal amplification (LAMP), respectively, found to be (3%, 95%CI: 2−3%, I2 = 0%) and (2%, 95%CI: 1−3%, I2 = 97.94%).Findings of the present study suggest high malaria positive incidence in the region. This implies that malaria control and elimination programmes towards malaria elimination could be negatively impacted and cause delays in actualising malaria elimination set dates. Further studies consisting of larger samples and continuous evaluation of malaria control programmes are recommended.

Analysis of a two-strain malaria transmission model with spatial heterogeneity and vector-bias

In this paper, we introduce a reaction-diffusion malaria model which incorporates vector-bias, spatial heterogeneity, sensitive and resistant strains. The main question that we study is the threshold dynamics of the model, in particular, whether the existence of spatial structure would allow two strains to coexist. In order to achieve this goal, we define the basic reproduction number [Formula: see text] and introduce the invasion reproduction number [Formula: see text] for strain [Formula: see text]. A quantitative analysis shows that if [Formula: see text], then disease-free steady state is globally asymptotically stable, while competitive exclusion, where strain i persists and strain j dies out, is a possible outcome when [Formula: see text] [Formula: see text], and a unique solution with two strains coexist to the model is globally asymptotically stable if [Formula: see text], [Formula: see text]. Numerical simulations reinforce these analytical results and demonstrate epidemiological interaction between two strains, discuss the influence of resistant strains and study the effects of vector-bias on the transmission of malaria.