Theory of reactive interventions in the elimination and control of malaria

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.

Testing and treatment for malaria elimination: a systematic review

BACKGROUND

Global interest in malaria elimination has prompted research on active test and treat (TaT) strategies.

METHODS

A systematic review and meta-analysis were conducted to assess the effectiveness of TaT strategies to reduce malaria transmission.

RESULTS

A total of 72 empirical research and 24 modelling studies were identified, mainly focused on proactive mass TaT (MTaT) and reactive case detection (RACD) in higher and lower transmission settings, respectively. Ten intervention studies compared MTaT to no MTaT and the evidence for impact on malaria incidence was weak. No intervention studies compared RACD to no RACD. Compared to passive case detection (PCD) alone, PCD + RACD using standard diagnostics increased infection detection 52.7% and 11.3% in low and very low transmission settings, respectively. Using molecular methods increased this detection of infections by 1.4- and 1.1-fold, respectively.

CONCLUSION

Results suggest MTaT is not effective for reducing transmission. By increasing case detection, surveillance data provided by RACD may indirectly reduce transmission by informing coordinated responses of intervention targeting.

Modelling the impact of interventions on imported, introduced and indigenous malaria infections in Zanzibar, Tanzania

Malaria cases can be classified as imported, introduced or indigenous cases. The World Health Organization's definition of malaria elimination requires an area to demonstrate that no new indigenous cases have occurred in the last three years. Here, we present a stochastic metapopulation model of malaria transmission that distinguishes between imported, introduced and indigenous cases, and can be used to test the impact of new interventions in a setting with low transmission and ongoing case importation. We use human movement and malaria prevalence data from Zanzibar, Tanzania, to parameterise the model. We test increasing the coverage of interventions such as reactive case detection; implementing new interventions including reactive drug administration and treatment of infected travellers; and consider the potential impact of a reduction in transmission on Zanzibar and mainland Tanzania. We find that the majority of new cases on both major islands of Zanzibar are indigenous cases, despite high case importation rates. Combinations of interventions that increase the number of infections treated through reactive case detection or reactive drug administration can lead to substantial decreases in malaria incidence, but for elimination within the next 40 years, transmission reduction in both Zanzibar and mainland Tanzania is necessary.

The impact of reactive case detection on malaria transmission in Zanzibar in the presence of human mobility

Malaria persists at low levels on Zanzibar despite the use of vector control and case management. We use a metapopulation model to investigate the role of human mobility in malaria persistence on Zanzibar, and the impact of reactive case detection. The model was parameterized using survey data on malaria prevalence, reactive case detection, and travel history. We find that in the absence of imported cases from mainland Tanzania, malaria would likely cease to persist on Zanzibar. We also investigate potential intervention scenarios that may lead to elimination, especially through changes to reactive case detection. While we find that some additional cases are removed by reactive case detection, a large proportion of cases are missed due to many infections having a low parasite density that go undetected by rapid diagnostic tests, a low rate of those infected with malaria seeking treatment, and a low rate of follow up at the household level of malaria cases detected at health facilities. While improvements in reactive case detection would lead to a reduction in malaria prevalence, none of the intervention scenarios tested here were sufficient to reach elimination. Imported cases need to be treated to have a substantial impact on prevalence.

Emulator-based Bayesian optimization for efficient multi-objective calibration of an individual-based model of malaria

Individual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose using a Bayesian optimization framework employing Gaussian process or machine learning emulator functions to calibrate a complex malaria transmission simulator. We demonstrate our approach by optimizing over a high-dimensional parameter space with respect to a portfolio of multiple fitting objectives built from datasets capturing the natural history of malaria transmission and disease progression. Our approach quickly outperforms previous calibrations, yielding an improved final goodness of fit. Per-objective parameter importance and sensitivity diagnostics provided by our approach offer epidemiological insights and enhance trust in predictions through greater interpretability.

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.

Spatial and genetic clustering of Plasmodium falciparum and Plasmodium vivax infections in a low-transmission area of Ethiopia

The distribution of malaria infections is heterogeneous in space and time, especially in low transmission settings. Understanding this clustering may allow identification and targeting of pockets of transmission. In Adama district, Ethiopia, Plasmodium falciparum and P. vivax malaria patients and controls were examined, together with household members and immediate neighbors. Rapid diagnostic test and quantitative PCR (qPCR) were used for the detection of infections that were genetically characterized by a panel of microsatellite loci for P. falciparum (26) and P. vivax (11), respectively. Individuals living in households of clinical P. falciparum patients were more likely to have qPCR detected P. falciparum infections (22.0%, 9/41) compared to individuals in control households (8.7%, 37/426; odds ratio, 2.9; 95% confidence interval, 1.3–6.4; P = .007). Genetically related P. falciparum, but not P. vivax infections showed strong clustering within households. Genotyping revealed a marked temporal cluster of P. falciparum infections, almost exclusively comprised of clinical cases. These findings uncover previously unappreciated transmission dynamics and support a rational approach to reactive case detection strategies for P. falciparum in Ethiopia.

Neurological disorder and psychosocial aspects of cerebral malaria: what is new on its pathogenesis and complications? A minireview

Recently, malaria is remain considered as the most prevalent infectious disease, affecting the human health globally. High morbidity and mortality worldwide is often allied with cerebral malaria (CM) based disorders of the central nervous system, especially across many tropical and sub-tropical regions. These disorders are characterised by the infection of Plasmodium species, which leads to acute or chronic neurological disorders, even after having active/effective antimalarial drugs. Furthermore, even during the treatment, individual remain sensitive for neurological impairments in the form of decrease blood flow and vascular obstruction in brain including many more other changes. This review briefly explains and update on the epidemiology, burden of disease, pathogenesis and role of CM in neurological disorders with behaviour and function in mouse and human models. Moreover, the social stigma, which plays an important role in neurological disorders and a factor for assessing CM, is also discussed in this review.

Molecular methods for tracking residual Plasmodium falciparum transmission in a close-to-elimination setting in Zanzibar

BACKGROUND

Molecular detection of low-density Plasmodium falciparum infections is essential for surveillance studies conducted to inform malaria control strategies in close-to-elimination settings. Molecular monitoring of residual malaria infections usually requires a large study size, therefore sampling and diagnostic processes need to be economical and optimized for high-throughput. A method comparison was undertaken to identify the most efficient diagnostic procedure for processing large collections of community samples with optimal test sensitivity, simplicity, and minimal costs.

METHODS

In a reactive case detection study conducted on Zanzibar, parasitaemia of 4590 individuals of all ages was investigated by a highly sensitive quantitative (q) PCR that targets multiple var gene copies per parasite genome. To reduce cost, a first round of positivity screening was performed on pools of dried blood spots from five individuals. Ten cycles of a pre-PCR were performed directly on the filter paper punches, followed by qPCR. In a second round, samples of positive pools were individually analysed by pre-PCR and qPCR.

RESULTS

Prevalence in household members and neighbors of index cases was 1.7% (78/4590) with a geometric mean parasite density of 58 parasites/µl blood. Using qPCR as gold standard, diagnostic sensitivity of rapid diagnostic tests (RDTs) was 37% (29/78). Infections positive by qPCR but negative by RDT had mean densities of 15 parasites/µl blood.

CONCLUSION

The approach of pre-screening reactive case detection samples in pools of five was ideal for a low prevalence setting such as in Zanzibar. Performing direct PCR on filter paper punches saves substantial time and justifies the higher cost for a polymerase suitable for amplifying DNA directly from whole blood. Molecular monitoring in community samples provided a more accurate picture of infection prevalence, as it identified a potential reservoir of infection that was largely missed by RDT. The developed qPCR-based methodology for screening large sample sets represents primarily a research tool that should inform the design of malaria elimination strategies. It may also prove beneficial for diagnostic tasks in surveillance-response activities.

Resurgence of malaria infection after mass treatment: a simulation study

BACKGROUND

Field studies are evaluating if mass drug administration (MDA) might shorten the time to elimination of Plasmodium falciparum malaria, when vector control measures and reactive surveillance strategies are scaled-up. A concern with this strategy is that there may be resurgence of transmission following MDA.

METHODS

A conceptual model was developed to classify possible outcomes of an initial period of MDA, followed by continuously implementing other interventions. The classification considered whether elimination or a new endemic stable state is achieved, and whether changes are rapid, transient, or gradual. These categories were informed by stability analyses of simple models of vector control, case management, and test-and-treat interventions. Individual-based stochastic models of malaria transmission (OpenMalaria) were then used to estimate the probability and likely rates of resurgence in realistic settings. Effects of concurrent interventions, including routine case management and test-and-treat strategies were investigated.

RESULTS

Analysis of the conceptual models suggest resurgence will occur after MDA unless transmission potential is very low, or the post-MDA prevalence falls below a threshold, which depends on both transmission potential and on the induction of bistability. Importation rates are important only when this threshold is very low. In most OpenMalaria simulations the approximately stable state achieved at the end of the simulations was independent of inclusion of MDA and the final state was unaffected by importation of infections at plausible rates. Elimination occurred only with high effective coverage of case management, low initial prevalence, and high intensity test-and-treat. High coverage of case management but not by test-and-treat induced bistability. Where resurgence occurred, its rate depended mainly on transmission potential (not treatment rates).

CONCLUSIONS

A short burst of high impact MDA is likely to be followed by resurgence. To avert resurgence, concomitant interventions need either to substantially reduce average transmission potential or to be differentially effective in averting or clearing infections at low prevalence. Case management at high effective coverage has this differential effect, and should suffice to avert resurgence caused by imported cases at plausible rates of importation. Once resurgence occurs, its rate depends mainly on transmission potential, not on treatment strategies.

Modelling reactive case detection strategies for interrupting transmission of Plasmodium falciparum malaria

BACKGROUND

As areas move closer to malaria elimination, a combination of limited resources and increasing heterogeneity in case distribution and transmission favour a shift to targeted reactive interventions. Reactive case detection (RCD), the following up of additional individuals surrounding an index case, has the potential to target transmission pockets and identify asymptomatic cases in them. Current RCD implementation strategies vary, and it is unclear which are most effective in achieving elimination.

METHODS

OpenMalaria, an established individual-based stochastic model, was used to simulate RCD in a Zambia-like setting. The capacity to follow up index cases, the search radius, the initial transmission and the case management coverage were varied. Suitable settings were identified and probabilities of elimination and time to elimination estimated. The value of routinely collected prevalence and incidence data for predicting the success of RCD was assessed.

RESULTS

The results indicate that RCD with the aim of transmission interruption is only appropriate in settings where initial transmission is very low (annual entomological inoculation rate (EIR) 1-2 or prevalence approx. < 7-19% depending on case management levels). Every index case needs to be followed up, up to a maximum case-incidence threshold which defines the suitability threshold of settings for elimination using RCD. Increasing the search radius around index cases is always beneficial.

CONCLUSIONS

RCD is highly resource intensive, requiring testing and treating of 400-500 people every week for 5-10 years for a reasonable chance of elimination in a Zambia-like setting.