Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study

Optimal Timing Regularly Outperforms Higher Coverage in Preventative Measles Supplementary Immunization Campaigns

Measles threatens the lives and livelihoods of tens of millions of children and there are countries where routine immunization systems miss enough individuals to create the risk of large outbreaks. To help address this threat, measles supplementary immunization activities are time-limited, coordinated campaigns to immunize en masse a target population. Timing campaigns to be concurrent with building outbreak risk is an important consideration, but current programmatic standards focus on campaigns achieving a high coverage of at least 95%. We show that there is a dramatic trade-off between campaign timeliness and coverage. Optimal timing at coverages as low as 50% for areas with weak routine immunization systems is shown to outperform the current standard, which is delayed by as little as 6 months. Measured coverage alone is revealed as a potentially misleading performance metric.

Reactive Case Detection and Treatment and Reactive Drug Administration for Reducing Malaria Transmission: A Systematic Review and Meta-Analysis

Many countries pursuing malaria elimination implement "reactive" strategies targeting household members and neighbors of index cases to reduce transmission. These strategies include reactive case detection and treatment (RACDT; testing and treating those positive) and reactive drug administration (RDA; providing antimalarials without testing). We conducted systematic reviews of RACDT and RDA to assess their effect on reducing malaria transmission and gathered evidence about key contextual factors important to their implementation. Two reviewers screened titles/abstracts and full-text records using defined criteria (Patient = those in malaria-endemic/receptive areas; Intervention = RACDT or RDA; Comparison = standard of care; Outcome = malaria incidence/prevalence) and abstracted data for meta-analyses. The Grading of Recommendations, Assessment, Development, and Evaluations approach was used to rate certainty of evidence (CoE) for each outcome. Of 1,460 records screened, reviewers identified five RACDT studies (three cluster-randomized controlled trials [cRCTs] and two nonrandomized studies [NRS]) and seven RDA studies (six cRCTs and one NRS); three cRCTs comparing RDA to RACDT were included in both reviews. Compared with RDA, RACDT was associated with nonsignificantly higher parasite prevalence (odds ratio [OR] = 1.85; 95% CI: 0.96-3.57; one study) and malaria incidence (rate ratio [RR] = 1.30; 95% CI: 0.94-1.79; three studies), both very low CoE. Compared with control or RACDT, RDA was associated with non-significantly lower parasite incidence (RR = 0.73; 95% CI: 0.36-1.47; 2 studies, moderate CoE), prevalence (OR = 0.78; 95% CI: 0.52-1.17; 4 studies, low CoE), and malaria incidence (RR = 0.93; 95% CI: 0.82-1.05; six studies, moderate CoE). Evidence for reactive strategies' impact on malaria transmission is limited, especially for RACDT, but suggests RDA might be more effective.

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.

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.

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.

Case-area targeted interventions (CATI) for reactive dengue control: Modelling effectiveness of vector control and prophylactic drugs in Singapore

BACKGROUND

Targeting interventions to areas that have recently experienced cases of disease is one strategy to contain outbreaks of infectious disease. Such case-area targeted interventions (CATI) have become an increasingly popular approach for dengue control but there is little evidence to suggest how precisely targeted or how recent cases need to be, to mount an effective response. The growing interest in the development of prophylactic and therapeutic drugs for dengue has also given new relevance for CATI strategies to interrupt transmission or deliver early treatment.

METHODS/PRINCIPAL FINDINGS

Here we develop a patch-based mathematical model of spatial dengue spread and fit it to spatiotemporal datasets from Singapore. Simulations from this model suggest CATI strategies could be effective, particularly if used in lower density areas. To maximise effectiveness, increasing the size of the radius around an index case should be prioritised even if it results in delays in the intervention being applied. This is partially because large intervention radii ensure individuals receive multiple and regular rounds of drug dosing or vector control, and thus boost overall coverage. Given equivalent efficacy, CATIs using prophylactic drugs are predicted to be more effective than adult mosquito-killing vector control methods and may even offer the possibility of interrupting individual chains of transmission if rapidly deployed. CATI strategies quickly lose their effectiveness if baseline transmission increases or case detection rates fall.

CONCLUSIONS/SIGNIFICANCE

These results suggest CATI strategies can play an important role in dengue control but are likely to be most relevant for low transmission areas where high coverage of other non-reactive interventions already exists. Controlled field trials are needed to assess the field efficacy and practical constraints of large operational CATI strategies.

Complexities in Defining the Unit of Intervention for Reactive Community-Based Malaria Treatment in the Gambia

With significant declines in malaria, infections are increasingly clustered in households, or groups of households where malaria transmission is higher than in surrounding household/villages. To decrease transmission in such cases, reactive interventions target household members of clinical malaria cases, with the intervention unit (e.g., the "household/s") derived from an epidemiological and operational perspective. A lack of unanimity regarding the spatial range of the intervention unit calls for greater importance to be placed on social context in conceptualizing the appropriate unit. A novel malaria elimination strategy based on reactive treatment was recently evaluated by a cluster randomized trial in a low transmission setting in The Gambia. Transdisciplinary research was used to assess and improve the effectiveness of the intervention which consisted, among others, of reflecting on whether the household was the most adequate unit of analysis. The intervention was piloted on the smallest treatment unit possible and was further adapted following a better understanding of the social and epidemiological context. Intervention units defined according to (i) shared sleeping spaces and (ii) household membership, showed substantial limitations as it was not possible to define them clearly and they were extremely variable within the study setting. Incorporating local definitions and community preference in the trial design led to the appropriate intervention unit-the compound-defined as an enclosed space containing one or several households belonging to the same extended patrilineal family. Our study demonstrates the appropriateness of using transdisciplinary research for investigating alternative intervention units that are better tailored to reactive treatment approaches.

Active Case Finding for Malaria: A 3-Year National Evaluation of Optimal Approaches to Detect Infections and Hotspots Through Reactive Case Detection in the Low-transmission Setting of Eswatini

Background

Reactive case detection (RACD) is a widely practiced malaria elimination intervention whereby close contacts of index cases receive malaria testing to inform treatment and other interventions. However, the optimal diagnostic and operational approaches for this resource-intensive strategy are not clear.

Methods

We conducted a 3-year prospective national evaluation of RACD in Eswatini, a malaria elimination setting. Loop-mediated isothermal amplification (LAMP) was compared to traditional rapid diagnostic testing (RDT) for the improved detection of infections and for hotspots (RACD events yielding ≥1 additional infection). The potential for index case–, RACD-, and individual-level factors to improve efficiencies was also evaluated.

Results

Among 377 RACD events, 10 890 participants residing within 500 m of index cases were tested. Compared to RDT, LAMP provided a 3-fold and 2.3-fold higher yield to detect infections (1.7% vs 0.6%) and hotspots (29.7% vs 12.7%), respectively. Hotspot detection improved with ≥80% target population coverage and response times within 7 days. Proximity to the index case was associated with a dose-dependent increased infection risk (up to 4-fold). Individual-, index case–, and other RACD-level factors were considered but the simple approach of restricting RACD to a 200-m radius maximized yield and efficiency.

Conclusions

We present the first large-scale national evaluation of optimal RACD approaches from a malaria elimination setting. To inform delivery of antimalarial drugs or other interventions, RACD, when conducted, should utilize more sensitive diagnostics and clear context-specific operational parameters. Future studies of RACD’s impact on transmission may still be needed.

Sustained Malaria Transmission despite Reactive Screen-and-Treat in a Low-Transmission Area of Southern Zambia

Malaria elimination strategies are designed to more effectively identify and treat infected individuals to interrupt transmission. One strategy, reactive screen-and-treat, starts with passive detection of symptomatic cases at health facilities. Individuals residing within the index case and neighboring households are screened with a malaria rapid diagnostic test (RDT) and treated if positive. However, it is unclear to what extent this strategy is effective in reducing transmission. Reactive screen-and-treat was implemented in Choma district, Southern Province, Zambia, in 2013, in which residents of the index case and neighboring households within 140 m were screened with an RDT. From March 2016 to July 2018, the screening radius was extended to 250-m, and additional follow-up visits at 30 and 90 days were added to evaluate the strategy. Plasmodium falciparum parasite prevalence was measured using an RDT and by quantitative PCR (qPCR). A 24-single nucleotide polymorphism molecular bar-code assay was used to genotype parasites. Eighty-four index case households with 676 residents were enrolled between March 2016 and March 2018. Within each season, parasite prevalence declined significantly in index households at the 30-day visit and remained low at the 90-day visit. However, parasite prevalence was not reduced to zero. Infections identified by qPCR persisted between study visits and were not identified by RDT. Parasites identified within the same household were most genetically related; however, overall parasite relatedness was low and similar across time and space. Thus, despite implementation of a reactive screen-and-treat program, parasitemia was not eliminated, and persisted in targeted households for at least 3 months.

Reactive Case Detection (RACD) and foci investigation strategies in malaria control and elimination: a review

Background

Reactive case detection (RACD) and foci investigation are key strategies in malaria elimination and prevention of its re-establishment. They are a key part of surveillance that has been recommended by the World Health Organization (WHO) to be considered as a core intervention and as one of the three pillars of the Global Technical Strategy for Malaria 2016–2030.

Methods

A search using the key words “Reactive Case Detection”, “RACD”, “RCD” and “Malaria” was carried out in PubMed, Scopus, Taylor and Francis online databases for studies published until 31st July 2019. The inclusion criteria for selection of articles for review included (1) how RACD is implemented in each country; (2) challenges faced in RACD implementation; (3) suggestions on how the effectiveness of RACD process can be improved.

Results

411 titles were identified, 41 full text articles were screened and 29 were found eligible for inclusion in the review. Published literature on RACD, and case and foci investigations has mostly assessed the process of the activity. Most studies have documented that the yield of positives in RACD has been highest in the index case’s household and the immediate neighbourhood of the index case. Microscopy and RDTs are the common tests used in RACD. The guidelines for case and foci investigation, and RACD and PACD, are not universally adopted and are country-specific. Some of the limitations and challenges identified include lack of proper guidelines, logistic issues and problems with public compliance.

Conclusions

Although there is no documented evidence that RACD is useful in malaria elimination settings, most authors have opined that RACD is necessary for malaria elimination. Lack of knowledge in the target populations, a target radius and how to carry out the RACD process is a major challenge in the decision-making process.

Costing malaria interventions from pilots to elimination programmes

Background

Malaria programmes in countries with low transmission levels require evidence to optimize deployment of current and new tools to reach elimination with limited resources. Recent pilots of elimination strategies in Ethiopia, Senegal, and Zambia produced evidence of their epidemiological impacts and costs. There is a need to generalize these findings to different epidemiological and health systems contexts.

Methods

Drawing on experience of implementing partners, operational documents and costing studies from these pilots, reference scenarios were defined for rapid reporting (RR), reactive case detection (RACD), mass drug administration (MDA), and in-door residual spraying (IRS). These generalized interventions from their trial implementation to one typical of programmatic delivery. In doing so, resource use due to interventions was isolated from research activities and was related to the pilot setting. Costing models developed around this reference implementation, standardized the scope of resources costed, the valuation of resource use, and the setting in which interventions were evaluated. Sensitivity analyses were used to inform generalizability of the estimates and model assumptions.

Results

Populated with local prices and resource use from the pilots, the models yielded an average annual economic cost per capita of $0.18 for RR, $0.75 for RACD, $4.28 for MDA (two rounds), and $1.79 for IRS (one round, 50% households). Intervention design and resource use at service delivery were key drivers of variation in costs of RR, MDA, and RACD. Scale was the most important parameter for IRS. Overall price level was a minor contributor, except for MDA where drugs accounted for 70% of the cost. The analyses showed that at implementation scales comparable to health facility catchment area, systematic correlations between model inputs characterizing implementation and setting produce large gradients in costs.

Conclusions

Prospective costing models are powerful tools to explore resource and cost implications of policy alternatives. By formalizing translation of operational data into an estimate of intervention cost, these models provide the methodological infrastructure to strengthen capacity gap for economic evaluation in endemic countries. The value of this approach for decision-making is enhanced when primary cost data collection is designed to enable analysis of the efficiency of operational inputs in relation to features of the trial or the setting, thus facilitating transferability.

A multiphase program for malaria elimination in southern Mozambique (the Magude project): A before-after study

BACKGROUND

Malaria eradication remains the long-term vision of the World Health Organization (WHO). However, whether malaria elimination is feasible in areas of stable transmission in sub-Saharan Africa with currently available tools remains a subject of debate. This study aimed to evaluate a multiphased malaria elimination project to interrupt Plasmodium falciparum malaria transmission in a rural district of southern Mozambique.

METHODS AND FINDINGS

A before-after study was conducted between 2015 and 2018 in the district of Magude, with 48,448 residents living in 10,965 households. Building on an enhanced surveillance system, two rounds of mass drug administrations (MDAs) per year over two years (phase I, August 2015-2017), followed by one year of reactive focal mass drug administrations (rfMDAs) (phase II, September 2017-June 2018) were deployed with annual indoor residual spraying (IRS), programmatically distributed long-lasting insecticidal nets (LLINs), and standard case management. The four MDA rounds covered 58%-72% of the population, and annual IRS reported coverage was >70%. Yearly parasite surveys and routine surveillance data were used to monitor the primary outcomes of the study-malaria prevalence and incidence-at baseline and annually since the onset of the project. Parasite prevalence by rapid diagnostic test (RDT) declined from 9.1% (95% confidence interval [CI] 7.0-11.8) in May 2015 to 2.6% (95% CI 2.0-3.4), representing a 71.3% (95% CI 71.1-71.4, p < 0.001) reduction after phase I, and to 1.4% (95% CI 0.9-2.2) after phase II. This represented an 84.7% (95% CI 81.4-87.4, p < 0.001) overall reduction in all-age prevalence. Case incidence fell from 195 to 75 cases per 1,000 during phase I (61.5% reduction) and to 67 per 1,000 during phase II (65.6% overall reduction). Interrupted time series (ITS) analysis was used to estimate the level and trend change in malaria cases associated with the set of project interventions and the number of cases averted. Phase I interventions were associated with a significant immediate reduction in cases of 69.1% (95% CI 57.5-77.6, p < 0.001). Phase II interventions were not associated with a level or trend change. An estimated 76.7% of expected cases were averted throughout the project (38,369 cases averted of 50,005 expected). One malaria-associated inpatient death was observed during the study period. There were 277 mild adverse events (AEs) recorded through the passive pharmacovigilance system during the four MDA rounds. One serious adverse event (SAE) that resulted in death was potentially related to the drug. The study was limited by the incomplete coverage of interventions, the quality of the routine and cross-sectional data collected, and the restricted accuracy of ITS analysis with a short pre-intervention period.

CONCLUSION

In this study, we observed that the interventions deployed during the Magude project fell short of interrupting P. falciparum transmission with the coverages achieved. While new tools and strategies may be required to eventually achieve malaria elimination in stable transmission areas of sub-Saharan Africa, this project showed that innovative mixes of interventions can achieve large reductions in disease burden, a necessary step in the pathway towards elimination.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02914145.

Association between the proportion of Plasmodium falciparum and Plasmodium vivax infections detected by passive surveillance and the magnitude of the asymptomatic reservoir in the community: a pooled analysis of paired health facility and community data

BACKGROUND

Passively collected malaria case data are the foundation for public health decision making. However, because of population-level immunity, infections might not always be sufficiently symptomatic to prompt individuals to seek care. Understanding the proportion of all Plasmodium spp infections expected to be detected by the health system becomes particularly paramount in elimination settings. The aim of this study was to determine the association between the proportion of infections detected and transmission intensity for Plasmodium falciparum and Plasmodium vivax in several global endemic settings.

METHODS

The proportion of infections detected in routine malaria data, P(Detect), was derived from paired household cross-sectional survey and routinely collected malaria data within health facilities. P(Detect) was estimated using a Bayesian model in 431 clusters spanning the Americas, Africa, and Asia. The association between P(Detect) and malaria prevalence was assessed using log-linear regression models. Changes in P(Detect) over time were evaluated using data from 13 timepoints over 2 years from The Gambia.

FINDINGS

The median estimated P(Detect) across all clusters was 12·5% (IQR 5·3-25·0) for P falciparum and 10·1% (5·0-18·3) for P vivax and decreased as the estimated log-PCR community prevalence increased (adjusted odds ratio [OR] for P falciparum 0·63, 95% CI 0·57-0·69; adjusted OR for P vivax 0·52, 0·47-0·57). Factors associated with increasing P(Detect) included smaller catchment population size, high transmission season, improved care-seeking behaviour by infected individuals, and recent increases (within the previous year) in transmission intensity.

INTERPRETATION

The proportion of all infections detected within health systems increases once transmission intensity is sufficiently low. The likely explanation for P falciparum is that reduced exposure to infection leads to lower levels of protective immunity in the population, increasing the likelihood that infected individuals will become symptomatic and seek care. These factors might also be true for P vivax but a better understanding of the transmission biology is needed to attribute likely reasons for the observed trend. In low transmission and pre-elimination settings, enhancing access to care and improvements in care-seeking behaviour of infected individuals will lead to an increased proportion of infections detected in the community and might contribute to accelerating the interruption of transmission.

FUNDING

Wellcome Trust.

Vector genetics, insecticide resistance and gene drives: An agent-based modeling approach to evaluate malaria transmission and elimination

Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness. Additionally, accelerated research and development of new tools that can be deployed alongside existing vector control strategies is key to eradicating malaria in the near future. Methods such as gene drives that aim to genetically modify large mosquito populations in the wild to either render them refractory to malaria or impair their reproduction may prove invaluable tools. Mathematical models of gene flow in populations, which is the transfer of genetic information from one population to another through migration, can offer invaluable insight into the behavior and potential impact of gene drives as well as the spread of insecticide resistance in the wild. Here, we present the first multi-locus, agent-based model of vector genetics that accounts for mutations and a many-to-many mapping cardinality of genotypes to phenotypes to investigate gene flow, and the propagation of gene drives in Anopheline populations. This model is embedded within a large scale individual-based model of malaria transmission representative of a high burden, high transmission setting characteristic of the Sahel. Results are presented for the selection of insecticide-resistant vectors and the spread of resistance through repeated deployment of insecticide treated nets (ITNs), in addition to scenarios where gene drives act in concert with existing vector control tools such as ITNs. The roles of seasonality, spatial distribution of vector habitat and feed sites, and existing vector control in propagating alleles that confer phenotypic traits via gene drives that result in reduced transmission are explored. The ability to model a spectrum of vector species with different genotypes and phenotypes in the context of malaria transmission allows us to test deployment strategies for existing interventions that reduce the deleterious effects of resistance and allows exploration of the impact of new tools being proposed or developed.

Country-Owned, Country-Driven: Perspectives from the World Health Organization on Malaria Elimination

Malaria has infected and killed humans since long before history began recording evidence of the parasite's pernicious influence. The extraordinary discoveries of the Plasmodium parasite by Charles Louis Alphonse Laveran in 1880, and the role of the Anopheles mosquito in transmission of the parasite to humans by Sir Ronald Ross in 1897, led to an understanding of the parasite life cycle and ultimately to the development of interventions that would interrupt disease transmission. Almost as soon as the insecticidal properties of dichlorodiphenyltrichloroethane (DDT) were discovered in 1939, the public health profession began battling to achieve a world free of malaria. That vision persists as the aim of all malariologists and, increasingly, the goal of all nations that remain endemic for malaria. This chapter recounts the history of malaria eradication and elimination efforts throughout the world and focuses on the current status of country-led and country-driven malaria elimination programs, along with the technical strategies recommended by the World Health Organization (WHO) for achievement of malaria elimination.

Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

BACKGROUND

More than ever, it is crucial to make the best use of existing country data, and analytical tools for developing malaria control strategies as the heterogeneity in malaria risk within countries is increasing, and the available malaria control tools are expanding while large funding gaps exist. Global and local policymakers, as well as funders, increasingly recognize the value of mathematical modelling as a strategic tool to support decision making. This case study article describes the long-term use of modelling in close collaboration with the National Malaria Control Programme (NMCP) in Tanzania, the challenges encountered and lessons learned.

CASE DESCRIPTION

In Tanzania, a recent rebound in prevalence led to the revision of the national malaria strategic plan with interventions targeted to the malaria risk at the sub-regional level. As part of the revision, a mathematical malaria modelling framework for setting specific predictions was developed and used between 2016 and 2019 to (1) reproduce setting specific historical malaria trends, and (2) to simulate in silico the impact of future interventions. Throughout the project, multiple stakeholder workshops were attended and the use of mathematical modelling interactively discussed.

EVALUATION

In Tanzania, the model application created an interdisciplinary and multisectoral dialogue platform between modellers, NMCP and partners and contributed to the revision of the national malaria strategic plan by simulating strategies suggested by the NMCP. The uptake of the modelling outputs and sustained interest by the NMCP were critically associated with following factors: (1) effective sensitization to the NMCP, (2) regular and intense communication, (3) invitation for the modellers to participate in the strategic plan process, and (4) model application tailored to the local context.

CONCLUSION

Empirical data analysis and its use for strategic thinking remain the cornerstone for evidence-based decision-making. Mathematical impact modelling can support the process both by unifying all stakeholders in one strategic process and by adding new key evidence required for optimized decision-making. However, without a long-standing partnership, it will be much more challenging to sensibilize programmes to the usefulness and sustained use of modelling and local resources within the programme or collaborating research institutions need to be mobilized.

Simulating the council-specific impact of anti-malaria interventions: A tool to support malaria strategic planning in Tanzania

INTRODUCTION

The decision-making process for malaria control and elimination strategies has become more challenging. Interventions need to be targeted at council level to allow for changing malaria epidemiology and an increase in the number of possible interventions. Models of malaria dynamics can support this process by simulating potential impacts of multiple interventions in different settings and determining appropriate packages of interventions for meeting specific expected targets.

METHODS

The OpenMalaria model of malaria dynamics was calibrated for all 184 councils in mainland Tanzania using data from malaria indicator surveys, school parasitaemia surveys, entomological surveillance, and vector control deployment data. The simulations were run for different transmission intensities per region and five interventions, currently or potentially included in the National Malaria Strategic Plan, individually and in combination. The simulated prevalences were fitted to council specific prevalences derived from geostatistical models to obtain council specific predictions of the prevalence and number of cases between 2017 and 2020. The predictions were used to evaluate in silico the feasibility of the national target of reaching a prevalence of below 1% by 2020, and to suggest alternative intervention stratifications for the country.

RESULTS

The historical prevalence trend was fitted for each council with an agreement of 87% in 2016 (95%CI: 0.84-0.90) and an agreement of 90% for the historical trend (2003-2016) (95%CI: 0.87-0.93) The current national malaria strategy was expected to reduce the malaria prevalence between 2016 and 2020 on average by 23.8% (95% CI: 19.7%-27.9%) if current case management levels were maintained, and by 52.1% (95% CI: 48.8%-55.3%) if the case management were improved. Insecticide treated nets and case management were the most cost-effective interventions, expected to reduce the prevalence by 25.0% (95% CI: 19.7%-30.2) and to avert 37 million cases between 2017 and 2020. Mass drug administration was included in most councils in the stratification selected for meeting the national target at minimal costs, expected to reduce the prevalence by 77.5% (95%CI: 70.5%-84.5%) and to avert 102 million cases, with almost twice higher costs than those of the current national strategy. In summary, the model suggested that current interventions are not sufficient to reach the national aim of a prevalence of less than 1% by 2020 and a revised strategic plan needs to consider additional, more effective interventions, especially in high transmission areas and that the targets need to be revisited.

CONCLUSION

The methodology reported here is based on intensive interactions with the NMCP and provides a helpful tool for assessing the feasibility of country specific targets and for determining which intervention stratifications at sub-national level will have most impact. This country-led application could support strategic planning of malaria control in many other malaria endemic countries.

Investigating the drivers of the spatio-temporal patterns of genetic differences between Plasmodium falciparum malaria infections in Kilifi County, Kenya

Knowledge of how malaria infections spread locally is important both for the design of targeted interventions aiming to interrupt malaria transmission and the design of trials to assess the interventions. A previous analysis of 1602 genotyped Plasmodium falciparum parasites in Kilifi, Kenya collected over 12 years found an interaction between time and geographic distance: the mean number of single nucleotide polymorphism (SNP) differences was lower for pairs of infections which were both a shorter time interval and shorter geographic distance apart. We determine whether the empiric pattern could be reproduced by a simple model, and what mean geographic distances between parent and offspring infections and hypotheses about genotype-specific immunity or a limit on the number of infections would be consistent with the data. We developed an individual-based stochastic simulation model of households, people and infections. We parameterized the model for the total number of infections, and population and household density observed in Kilifi. The acquisition of new infections, mutation, recombination, geographic location and clearance were included. We fit the model to the observed numbers of SNP differences between pairs of parasite genotypes. The patterns observed in the empiric data could be reproduced. Although we cannot rule out genotype-specific immunity or a limit on the number of infections per individual, they are not necessary to account for the observed patterns. The mean geographic distance between parent and offspring malaria infections for the base model was 0.5 km (95% CI 0.3-1.5), for a distribution with 68% of distances shorter than the mean. Very short mean distances did not fit well, but mixtures of distributions were also consistent with the data. For a pathogen which undergoes meiosis in a setting with moderate transmission and a low coverage of infections, analytic methods are limited but an individual-based model can be used with genotyping data to estimate parameter values and investigate hypotheses about underlying processes.

Evaluating Response Time in Zanzibar's Malaria Elimination Case-Based Surveillance-Response System

As countries transition toward malaria elimination, malaria programs rely on surveillance-response systems, which are often supported by web- and mobile phone-based reporting tools. Such surveillance-response systems are interventions for elimination, making it important to determine if they are operating optimally. A metric to measure this by is timeliness. This study used a mixed-methods approach to investigate the response time of Zanzibar's malaria elimination surveillance-response system, Malaria Case Notification (MCN). MCN conducts both passive and reactive case detection, supported by a mobile phone-based reporting tool called Coconut Surveillance. Using data obtained from RTI International and the Zanzibar Malaria Elimination Program (ZAMEP), analysis of summary statistics was conducted to investigate the association of response time with geography, and time series techniques were used to investigate trends in response time and its association with the number of reported cases. Results indicated that response time varied by the district in Zanzibar (0.6-6.05 days) and that it was not associated with calendar time or the number of reported cases. Survey responses and focus groups with a cadre of health workers, district malaria surveillance officers, shed light on operational challenges faced during case investigation, such as incomplete health records and transportation issues, which stem from deficiencies in aspects of ZAMEP's program management. These findings illustrate that timely response for malaria elimination depends on effective program management, despite the automation of web-based or mobile phone-based tools. For surveillance-response systems to work optimally, malaria programs should ensure that optimal management practices are in place.

Implementation and applications of EMOD, an individual-based multi-disease modeling platform

Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach developed with formal software support. The epidemiological modeling software, EMOD, has undergone a decade of software development. It is structured so that a majority of code is shared across disease modeling including malaria, HIV, tuberculosis, dengue, polio and typhoid. In additional to implementation efficiency, the sharing increases code usage and testing. The freely available codebase also includes hundreds of regression tests, scientific feature tests and component tests to help verify functionality and avoid inadvertent changes to functionality during future development. Here we describe the levels of detail, flexible configurability and modularity enabled by EMOD and the role of software development principles and processes in its development.

Theory of reactive interventions in the elimination and control of malaria

Background

Reactive case detection (RCD) is an integral part of many malaria control and elimination programmes and can be conceived of as a way of gradually decreasing transmission. However, it is unclear under what circumstances RCD may have a substantial impact on prevalence, how likely it is to lead to local elimination, or how effective it needs to be to prevent reintroduction after transmission has been interrupted.

Methods

Analyses and simulations of a discrete time compartmental susceptible-infectious-susceptible (SIS) model were used to understand the mechanisms of how RCD changes transmission dynamics and estimate the impact of RCD programmes in a range of settings with varying patterns of transmission potential and programme characteristics. Prevalence survey data from recent studies in Zambia were used to capture the effects of spatial clustering of patent infections.

Results

RCD proved most effective at low prevalence. Increasing the number of index cases followed was more important than increasing the number of neighbours tested per index case. Elimination was achieved only in simulations of situations with very low transmission intensity and following many index cases. However, RCD appears to be helpful in maintaining the disease-free state after achieving malaria elimination (through other interventions).

Conclusion

RCD alone can eliminate malaria in only a very limited range of settings, where transmission potential is very low, and improving the coverage of RCD has little effect on this range. In other settings, it is likely to reduce disease burden. RCD may also help maintain the disease-free state in the face of imported infections. Prevalence survey data can be used to estimate a targeting ratio (the ratio of prevalence found through RCD to that in the general population) which is an important determinant of the effect of RCD.

Electronic supplementary material

The online version of this article (10.1186/s12936-019-2882-z) contains supplementary material, which is available to authorized users.

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.

Model selection for hybrid dynamical systems via sparse regression

Hybrid systems are traditionally difficult to identify and analyse using classical dynamical systems theory. Moreover, recently developed model identification methodologies largely focus on identifying a single set of governing equations solely from measurement data. In this article, we develop a new methodology, Hybrid-Sparse Identification of Nonlinear Dynamics, which identifies separate nonlinear dynamical regimes, employs information theory to manage uncertainty and characterizes switching behaviour. Specifically, we use the nonlinear geometry of data collected from a complex system to construct a set of coordinates based on measurement data and augmented variables. Clustering the data in these measurement-based coordinates enables the identification of nonlinear hybrid systems. This methodology broadly empowers nonlinear system identification without constraining the data locally in time and has direct connections to hybrid systems theory. We demonstrate the success of this method on numerical examples including a mass–spring hopping model and an infectious disease model. Characterizing complex systems that switch between dynamic behaviours is integral to overcoming modern challenges such as eradication of infectious diseases, the design of efficient legged robots and the protection of cyber infrastructures.

Impact of mass drug administration campaigns depends on interaction with seasonal human movement

Background

Mass drug administration (MDA) is a control and elimination tool for treating infectious diseases. For malaria, it is widely accepted that conducting MDA during the dry season results in the best outcomes. However, seasonal movement of populations into and out of MDA target areas is common in many places and could potentially fundamentally limit the ability of MDA campaigns to achieve elimination.

Methods

A mathematical model was used to simulate malaria transmission in two villages connected to a high-risk area into and out of which 10% of villagers traveled seasonally. MDA was given only in the villages. Prevalence reduction under various possible timings of MDA and seasonal travel was predicted.

Results

MDA is most successful when distributed outside the traveling season and during the village low-transmission season. MDA is least successful when distributed during the traveling season and when traveling overlaps with the peak transmission season in the high-risk area. Mistiming MDA relative to seasonal travel resulted in much poorer outcomes than mistiming MDA relative to the peak transmission season within the villages.

Conclusions

Seasonal movement patterns of high-risk groups should be taken into consideration when selecting the optimum timing of MDA campaigns.

Do hotspots fuel malaria transmission: a village-scale spatio-temporal analysis of a 2-year cohort study in The Gambia

BACKGROUND

Despite the biological plausibility of hotspots fueling malaria transmission, the evidence to support this concept has been mixed. If transmission spreads from high burden to low burden households in a consistent manner, then this could have important implications for control and elimination program development.

METHODS

Data from a longitudinal cohort in The Gambia was analyzed. All consenting individuals residing in 12 villages across the country were sampled monthly from June (dry season) to December 2013 (wet season), in April 2014 (mid dry season), and monthly from June to December 2014. A study nurse stationed within each village recorded passively detected malaria episodes between visits. Plasmodium falciparum infections were determined by polymerase chain reaction and analyzed using a geostatistical model.

RESULTS

Household-level observed monthly incidence ranged from 0 to 0.50 infection per person (interquartile range = 0.02-0.10) across the sampling months, and high burden households exist across all study villages. There was limited evidence of a spatio-temporal pattern at the monthly timescale irrespective of transmission intensity. Within-household transmission was the most plausible hypothesis examined to explain the observed heterogeneity in infections.

CONCLUSIONS

Within-village malaria transmission patterns are concentrated in a small proportion of high burden households, but patterns are stochastic regardless of endemicity. Our findings support the notion of transmission occurring at the household and village scales but not the use of a targeted approach to interrupt spreading of infections from high to low burden areas within villages in this setting.

Agent-based models of malaria transmission: a systematic review

BACKGROUND

Much of the extensive research regarding transmission of malaria is underpinned by mathematical modelling. Compartmental models, which focus on interactions and transitions between population strata, have been a mainstay of such modelling for more than a century. However, modellers are increasingly adopting agent-based approaches, which model hosts, vectors and/or their interactions on an individual level. One reason for the increasing popularity of such models is their potential to provide enhanced realism by allowing system-level behaviours to emerge as a consequence of accumulated individual-level interactions, as occurs in real populations.

METHODS

A systematic review of 90 articles published between 1998 and May 2018 was performed, characterizing agent-based models (ABMs) relevant to malaria transmission. The review provides an overview of approaches used to date, determines the advantages of these approaches, and proposes ideas for progressing the field.

RESULTS

The rationale for ABM use over other modelling approaches centres around three points: the need to accurately represent increased stochasticity in low-transmission settings; the benefits of high-resolution spatial simulations; and heterogeneities in drug and vaccine efficacies due to individual patient characteristics. The success of these approaches provides avenues for further exploration of agent-based techniques for modelling malaria transmission. Potential extensions include varying elimination strategies across spatial landscapes, extending the size of spatial models, incorporating human movement dynamics, and developing increasingly comprehensive parameter estimation and optimization techniques.

CONCLUSION

Collectively, the literature covers an extensive array of topics, including the full spectrum of transmission and intervention regimes. Bringing these elements together under a common framework may enhance knowledge of, and guide policies towards, malaria elimination. However, because of the diversity of available models, endorsing a standardized approach to ABM implementation may not be possible. Instead it is recommended that model frameworks be contextually appropriate and sufficiently described. One key recommendation is to develop enhanced parameter estimation and optimization techniques. Extensions of current techniques will provide the robust results required to enhance current elimination efforts.

How Far Are We from Reaching Universal Malaria Testing of All Fever Cases?

Universal malaria diagnostic testing of all fever cases is the first step in correct malaria case management. However, monitoring adherence to universal testing is complicated by unreliable recording and reporting of the true number of fever cases. We searched the literature to obtain gold-standard estimates for the proportion of patients attending outpatient clinics in sub-Saharan Africa with malarial and non-malarial febrile illness. To correct for differences in malaria transmission, we calculated the proportion of patients with fever after excluding confirmed malaria cases. Next, we analyzed routine data from Guinea and Senegal to calculate the proportion of outpatients tested after exclusion of confirmed malaria cases from the numerator and denominator. From 12 health facility surveys in sub-Saharan Africa with gold-standard fever screening, the median proportion of febrile illness among outpatients after exclusion of confirmed malaria fevers was 57% (range: 46-80%). Analysis of routine data after exclusion of confirmed malaria cases demonstrated much lower testing proportions of 23% (Guinea) and 13% (Senegal). There was substantial spatial and temporal heterogeneity in this testing proportion, and testing in Senegal was correlated with malaria season. Given the evidence from gold-standard surveys that at least 50% of non-malaria consultations in sub-Saharan Africa are for febrile illness, it appears that a substantial proportion of patients with fever are not tested for malaria in health facilities when considering routine data. Tracking the proportion of patients tested for malaria after exclusion of the confirmed malaria cases could allow programs to make inferences about malaria testing practices using routine data.

Pathway to Deployment of Gene Drive Mosquitoes as a Potential Biocontrol Tool for Elimination of Malaria in Sub-Saharan Africa: Recommendations of a Scientific Working Group†

Gene drive technology offers the promise for a high-impact, cost-effective, and durable method to control malaria transmission that would make a significant contribution to elimination. Gene drive systems, such as those based on clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated protein, have the potential to spread beneficial traits through interbreeding populations of malaria mosquitoes. However, the characteristics of this technology have raised concerns that necessitate careful consideration of the product development pathway. A multidisciplinary working group considered the implications of low-threshold gene drive systems on the development pathway described in the World Health Organization Guidance Framework for testing genetically modified (GM) mosquitoes, focusing on reduction of malaria transmission by Anopheles gambiae s.l. mosquitoes in Africa as a case study. The group developed recommendations for the safe and ethical testing of gene drive mosquitoes, drawing on prior experience with other vector control tools, GM organisms, and biocontrol agents. These recommendations are organized according to a testing plan that seeks to maximize safety by incrementally increasing the degree of human and environmental exposure to the investigational product. As with biocontrol agents, emphasis is placed on safety evaluation at the end of physically confined laboratory testing as a major decision point for whether to enter field testing. Progression through the testing pathway is based on fulfillment of safety and efficacy criteria, and is subject to regulatory and ethical approvals, as well as social acceptance. The working group identified several resources that were considered important to support responsible field testing of gene drive mosquitoes.

Mapping multiple components of malaria risk for improved targeting of elimination interventions

There is a long history of considering the constituent components of malaria risk and the malaria transmission cycle via the use of mathematical models, yet strategic planning in endemic countries tends not to take full advantage of available disease intelligence to tailor interventions. National malaria programmes typically make operational decisions about where to implement vector control and surveillance activities based upon simple categorizations of annual parasite incidence. With technological advances, an enormous opportunity exists to better target specific malaria interventions to the places where they will have greatest impact by mapping and evaluating metrics related to a variety of risk components, each of which describes a different facet of the transmission cycle. Here, these components and their implications for operational decision-making are reviewed. For each component, related mappable malaria metrics are also described which may be measured and evaluated by malaria programmes seeking to better understand the determinants of malaria risk. Implementing tailored programmes based on knowledge of the heterogeneous distribution of the drivers of malaria transmission rather than only consideration of traditional metrics such as case incidence has the potential to result in substantial improvements in decision-making. As programmes improve their ability to prioritize their available tools to the places where evidence suggests they will be most effective, elimination aspirations may become increasingly feasible.