Philip A. Eckhoff

Dynamics of the Human Infectious Reservoir for Malaria Determined by Mosquito Feeding Assays and Ultrasensitive Malaria Diagnosis in Burkina Faso

BACKGROUND Plasmodium falciparum gametocytes are essential for malaria transmission. Malaria control measures that aim at reducing transmission require an accurate characterization of the human infectious reservoir. METHODS We longitudinally determined human infectiousness to mosquitoes and P. falciparum carriage by an ultrasensitive RNA-based diagnostics in 130 randomly selected inhabitants of an endemic area. RESULTS At least 1 mosquito was infected by 32.6% (100 of 307) of the blood samples; in total, 7.6% of mosquitoes (916 of 12 079) were infected. The proportion of infectious individuals and infected mosquitoes were negatively associated with age and positively with asexual parasites (P < .001). Human infectiousness was higher at the start of the wet season and subsequently declined at the peak of the wet season (adjusted odds ratio, 0.52; P = .06) and in the dry season (0.23; P < .001). Overall, microscopy-negative individuals were responsible for 28.7% of infectious individuals (25 of 87) and 17.0% of mosquito infections (145 of 855). CONCLUSIONS Our study reveals that the infectious reservoir peaks at the start of the wet season, with prominent roles for infections in children and submicroscopic infections. These findings have important consequences for strategies and the timing of interventions, which need to include submicroscopic infections and be implemented in the dry season.

Oral, ultra–long-lasting drug delivery: Application toward malaria elimination goals

A newly developed platform capable of oral, ultra–long-acting drug delivery could be applied against the malaria vector in elimination programs. Toward malaria eradication Although we know how to prevent malaria, we have failed to eliminate this damaging disease. To help the millions of individuals still affected around the world, Bellinger et al. have designed an easy-to-administer device that provides long-lasting delivery of an antimalarial drug. A star-shaped, drug-containing material is packaged into a capsule. When swallowed, the capsule dissolves in the stomach, and the star unfolds, assuming a shape that cannot pass further down the intestine. The star delivers a drug toxic to malaria-carrying mosquitoes for weeks but eventually falls apart and passes harmlessly out of the body. Modeling studies show that long-term delivery of this drug may move us closer to the elimination of this problematic disease by improving patient adherence to treatment. Efforts at elimination of scourges, such as malaria, are limited by the logistic challenges of reaching large rural populations and ensuring patient adherence to adequate pharmacologic treatment. We have developed an oral, ultra–long-acting capsule that dissolves in the stomach and deploys a star-shaped dosage form that releases drug while assuming a geometry that prevents passage through the pylorus yet allows passage of food, enabling prolonged gastric residence. This gastric-resident, drug delivery dosage form releases small-molecule drugs for days to weeks and potentially longer. Upon dissolution of the macrostructure, the components can safely pass through the gastrointestinal tract. Clinical, radiographic, and endoscopic evaluation of a swine large-animal model that received these dosage forms showed no evidence of gastrointestinal obstruction or mucosal injury. We generated long-acting formulations for controlled release of ivermectin, a drug that targets malaria-transmitting mosquitoes, in the gastric environment and incorporated these into our dosage form, which then delivered a sustained therapeutic dose of ivermectin for up to 14 days in our swine model. Further, by using mathematical models of malaria transmission that incorporate the lethal effect of ivermectin against malaria-transmitting mosquitoes, we demonstrated that this system will boost the efficacy of mass drug administration toward malaria elimination goals. Encapsulated, gastric-resident dosage forms for ultra–long-acting drug delivery have the potential to revolutionize treatment options for malaria and other diseases that affect large populations around the globe for which treatment adherence is essential for efficacy.

Mass campaigns with antimalarial drugs: a modelling comparison of artemether-lumefantrine and DHA-piperaquine with and without primaquine as tools for malaria control and elimination

BackgroundAntimalarial drugs are a powerful tool for malaria control and elimination. Artemisinin-based combination therapies (ACTs) can reduce transmission when widely distributed in a campaign setting. Modelling mass antimalarial campaigns can elucidate how to most effectively deploy drug-based interventions and quantitatively compare the effects of cure, prophylaxis, and transmission-blocking in suppressing parasite prevalence.MethodsA previously established agent-based model that includes innate and adaptive immunity was used to simulate malaria infections and transmission. Pharmacokinetics of artemether, lumefantrine, dihydroartemisinin, piperaquine, and primaquine were modelled with a double-exponential distribution-elimination model including weight-dependent parameters and age-dependent dosing. Drug killing of asexual parasites and gametocytes was calibrated to clinical data. Mass distribution of ACTs and primaquine was simulated with seasonal mosquito dynamics at a range of transmission intensities.ResultsA single mass campaign with antimalarial drugs is insufficient to permanently reduce malaria prevalence when transmission is high. Current diagnostics are insufficiently sensitive to accurately identify asymptomatic infections, and mass-screen-and-treat campaigns are much less efficacious than mass drug administrations. Improving campaign coverage leads to decreased prevalence one month after the end of the campaign, while increasing compliance lengthens the duration of protection against reinfection. Use of a long-lasting prophylactic as part of a mass drug administration regimen confers the most benefit under conditions of high transmission and moderately high coverage. Addition of primaquine can reduce prevalence but exerts its largest effect when coupled with a long-lasting prophylactic.ConclusionsMass administration of antimalarial drugs can be a powerful tool to reduce prevalence for a few months post-campaign. A slow-decaying prophylactic administered with a parasite-clearing drug offers strong protection against reinfection, especially in highly endemic areas. Transmission-blocking drugs have only limited effects unless administered with a prophylactic under very high coverage.

Impact of mosquito gene drive on malaria elimination in a computational model with explicit spatial and temporal dynamics

Significance Gene drive mosquitoes have tremendous potential to help eliminate malaria, and multiple gene drive approaches have recently shown promise in laboratory settings. These approaches include population suppression through fertility disruption, driving-Y chromosomes, and population replacement with genes that limit malaria transmission. Mathematical modeling is used to evaluate these approaches by simulating realistic field settings with seasonality to determine constraints on construct parameters and release strategies. Parameter variation from simulation baselines captures much of sub-Saharan African epidemiology and shows high potential for gene drive constructs to provide transformational tools to facilitate elimination of malaria, even in the most challenging settings. This analysis provides insights into performance characteristics necessary for each approach to succeed that can inform their further development. The renewed effort to eliminate malaria and permanently remove its tremendous burden highlights questions of what combination of tools would be sufficient in various settings and what new tools need to be developed. Gene drive mosquitoes constitute a promising set of tools, with multiple different possible approaches including population replacement with introduced genes limiting malaria transmission, driving-Y chromosomes to collapse a mosquito population, and gene drive disrupting a fertility gene and thereby achieving population suppression or collapse. Each of these approaches has had recent success and advances under laboratory conditions, raising the urgency for understanding how each could be deployed in the real world and the potential impacts of each. New analyses are needed as existing models of gene drive primarily focus on nonseasonal or nonspatial dynamics. We use a mechanistic, spatially explicit, stochastic, individual-based mathematical model to simulate each gene drive approach in a variety of sub-Saharan African settings. Each approach exhibits a broad region of gene construct parameter space with successful elimination of malaria transmission due to the targeted vector species. The introduction of realistic seasonality in vector population dynamics facilitates gene drive success compared with nonseasonal analyses. Spatial simulations illustrate constraints on release timing, frequency, and spatial density in the most challenging settings for construct success. Within its parameter space for success, each gene drive approach provides a tool for malaria elimination unlike anything presently available. Provided potential barriers to success are surmounted, each achieves high efficacy at reducing transmission potential and lower delivery requirements in logistically challenged settings.

Discovering dynamic patterns from infectious disease data using dynamic mode decomposition

Background The development and application of quantitative methods to understand disease dynamics and plan interventions is becoming increasingly important in the push toward eradication of human infectious diseases, exemplified by the ongoing effort to stop the spread of poliomyelitis. Methods Dynamic mode decomposition (DMD) is a recently developed method focused on discovering coherent spatial-temporal modes in high-dimensional data collected from complex systems with time dynamics. The algorithm has a number of advantages including a rigorous connection to the analysis of nonlinear systems, an equation-free architecture, and the ability to efficiently handle high-dimensional data. Results We demonstrate the method on three different infectious disease sets including Google Flu Trends data, pre-vaccination measles in the UK, and paralytic poliomyelitis wild type-1 cases in Nigeria. For each case, we describe the utility of the method for surveillance and resource allocation. Conclusions We demonstrate how DMD can aid in the analysis of spatial-temporal disease data. DMD is poised to be an effective and efficient computational analysis tool for the study of infectious disease.

A mathematical model of the impact of present and future malaria vaccines

BackgroundWith the encouraging advent of new malaria vaccine candidates, mathematical modelling of expected impacts of present and future vaccines as part of multi-intervention strategies is especially relevant.MethodsThe impact of potential malaria vaccines is presented utilizing the EMOD model, a comprehensive model of the vector life cycle coupled to a detailed mechanistic representation of intra-host parasite and immune dynamics. Values of baseline transmission and vector feeding behaviour parameters are identified, for which local elimination is enabled by layering pre-erythrocytic vaccines of various efficacies on top of high and sustained insecticide-treated net coverage. The expected reduction in clinical cases is further explored in a scenario that targets children by adding a pre-erythrocytic vaccine to the EPI programme for newborns.ResultsAt high transmission, there is a minimal reduction in clinical disease cases, as the time to infection is only slightly delayed. At lower transmission, there is an accelerating community-level protection that has subtle dependences on heterogeneities in vector behaviour, ecology, and intervention coverage. At very low transmission, the trend reverses as many children are vaccinated to prevent few cases.ConclusionsThe maximum-impact setting is one in which the impact of increasing bed net coverage has saturated, vector feeding is primarily outdoors, and transmission is just above the threshold where small perturbations from a vaccine intervention result in large community benefits.

Characterization of the infectious reservoir of malaria with an agent-based model calibrated to age-stratified parasite densities and infectiousness

BackgroundElimination of malaria can only be achieved through removal of all vectors or complete depletion of the infectious reservoir in humans. Mechanistic models can be built to synthesize diverse observations from the field collected under a variety of conditions and subsequently used to query the infectious reservoir in great detail.MethodsThe EMOD model of malaria transmission was calibrated to prevalence, incidence, asexual parasite density, gametocyte density, infection duration, and infectiousness data from nine study sites. The infectious reservoir was characterized by age and parasite detectability with diagnostics of varying sensitivity over a range of transmission intensities with and without case management and vector control. Mass screen-and-treat drug campaigns were tested for likelihood of achieving elimination.ResultsThe composition of the infectious reservoir is similar over a range of transmission intensities, and higher intensity settings are biased towards infections in children. Recent ramp-ups in case management and use of insecticide-treated bed nets (ITNs) reduce the infectious reservoir and shift the composition towards sub-microscopic infections. Mass campaigns with anti-malarial drugs are highly effective at interrupting transmission if deployed shortly after ITN campaigns.ConclusionsLow-density infections comprise a substantial portion of the infectious reservoir. Proper timing of vector control, seasonal variation in transmission intensity and mass drug campaigns allows lingering population immunity to help drive a region towards elimination.

Predictive spatial risk model of poliovirus to aid prioritization and hasten eradication in Nigeria

BackgroundOne of the challenges facing the Global Polio Eradication Initiative is efficiently directing limited resources, such as specially trained personnel, community outreach activities, and satellite vaccinator tracking, to the most at-risk areas to maximize the impact of interventions. A validated predictive model of wild poliovirus circulation would greatly inform prioritization efforts by accurately forecasting areas at greatest risk, thus enabling the greatest effect of program interventions.MethodsUsing Nigerian acute flaccid paralysis surveillance data from 2004-2013, we developed a spatial hierarchical Poisson hurdle model fitted within a Bayesian framework to study historical polio caseload patterns and forecast future circulation of type 1 and 3 wild poliovirus within districts in Nigeria. A Bayesian temporal smoothing model was applied to address data sparsity underlying estimates of covariates at the district level.ResultsWe find that calculated vaccine-derived population immunity is significantly negatively associated with the probability and number of wild poliovirus case(s) within a district. Recent case information is significantly positively associated with probability of a case, but not the number of cases. We used lagged indicators and coefficients from the fitted models to forecast reported cases in the subsequent six-month periods. Over the past three years, the average predictive ability is 86 ± 2% and 85 ± 4% for wild poliovirus type 1 and 3, respectively. Interestingly, the predictive accuracy of historical transmission patterns alone is equivalent (86 ± 2% and 84 ± 4% for type 1 and 3, respectively). We calculate uncertainty in risk ranking to inform assessments of changes in rank between time periods.ConclusionsThe model developed in this study successfully predicts districts at risk for future wild poliovirus cases in Nigeria. The highest predicted district risk was 12.8 WPV1 cases in 2006, while the lowest district risk was 0.001 WPV1 cases in 2013. Model results have been used to direct the allocation of many different interventions, including political and religious advocacy visits. This modeling approach could be applied to other vaccine preventable diseases for use in other control and elimination programs.

Dropout and re-enrollment: implications for epidemiological projections of treatment programs.

Objective:EMOD-HIV v0.8 has been used to estimate the potential impact of expanding treatment guidelines to allow earlier initiation of antiretroviral therapy (ART) in sub-Saharan Africa with current or improved treatment coverage. In generating these results, a model must additionally make assumptions about the rates of dropout and re-initiation into ART programs before and after the program change, about which little is known. The objective of this work is to rigorously analyze modeling assumptions and the sensitivity of model results with respect to relevant mechanisms and parameters. Methods:We varied key model assumptions pertaining to ART dropout and re-enrollment to analyze their effect on the cost, impact, and cost-effectiveness of expanding treatment guidelines, and of expanding coverage via improved testing and linkage to care. Additionally, we performed a sensitivity analysis of 17 relevant model parameters. Setting:South Africa. Results:Allowing re-initiation of ART irrespective of prior treatment doubled the cost and impact of expanding treatment guidelines, as compared with a scenario in which re-initiation could only be triggered by a health event (AIDS symptoms, diagnosis of a partner, or an antenatal care visit). Increasing the probability of ‘voluntary’ re-initiation (not triggered by a health event) was the most cost-effective way to improve the treatment program, especially in the short term because it provided immediate benefits to those who would otherwise have delayed re-initiation until the onset of AIDS symptoms. However, the maximum impact of this change was limited compared with expanding coverage through improvements in testing and linkage to care. Beyond improvements in coverage and re-initiation, further gains could be made by improving retention in care. Only with optimal retention in care was expansion of guidelines cost-saving after 20 years due to reductions in transmission. Re-initiation did not reduce transmission sufficiently to make a guideline change cost-effective due to transmission that occurred while patients were away from care. Sensitivity analysis suggested that enormous health benefits could be attained by improving treatment regimens to have higher efficacy at preventing transmission, increasing the proportion of the population with access to improved healthcare, and reducing ‘leaks’ in the ‘cascade of care.’ Increasing the proportion of individuals who receive CD4+ cell results was particularly cost-effective at baseline levels of coverage, and increasing retention on ART was particularly cost-effective with expanded coverage. Conclusion:This analysis provides a sense of the magnitude of uncertainty in program cost and impact that policy-makers could anticipate in the face of uncertain future programmatic changes. Our findings suggest that increasing re-initiation is the most cost-effective means of initial program improvement, especially in the short term, but that improvements in retention are necessary in order to reap the full transmission-blocking benefits of a test-and-treat program in the long term.

Optimal Population-Level Infection Detection Strategies for Malaria Control and Elimination in a Spatial Model of Malaria Transmission

Mass campaigns with antimalarial drugs are potentially a powerful tool for local elimination of malaria, yet current diagnostic technologies are insufficiently sensitive to identify all individuals who harbor infections. At the same time, overtreatment of uninfected individuals increases the risk of accelerating emergence of drug resistance and losing community acceptance. Local heterogeneity in transmission intensity may allow campaign strategies that respond to index cases to successfully target subpatent infections while simultaneously limiting overtreatment. While selective targeting of hotspots of transmission has been proposed as a strategy for malaria control, such targeting has not been tested in the context of malaria elimination. Using household locations, demographics, and prevalence data from a survey of four health facility catchment areas in southern Zambia and an agent-based model of malaria transmission and immunity acquisition, a transmission intensity was fit to each household based on neighborhood age-dependent malaria prevalence. A set of individual infection trajectories was constructed for every household in each catchment area, accounting for heterogeneous exposure and immunity. Various campaign strategies—mass drug administration, mass screen and treat, focal mass drug administration, snowball reactive case detection, pooled sampling, and a hypothetical serological diagnostic—were simulated and evaluated for performance at finding infections, minimizing overtreatment, reducing clinical case counts, and interrupting transmission. For malaria control, presumptive treatment leads to substantial overtreatment without additional morbidity reduction under all but the highest transmission conditions. Compared with untargeted approaches, selective targeting of hotspots with drug campaigns is an ineffective tool for elimination due to limited sensitivity of available field diagnostics. Serological diagnosis is potentially an effective tool for malaria elimination but requires higher coverage to achieve similar results to mass distribution of presumptive treatment.