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Sustainable reductions in African malaria transmission require innovative tools for mosquito control. One proposal involves the use of low-threshold gene drive in Anopheles vector species, where a 'causal pathway' would be initiated by (i) the release of a gene drive system in target mosquito vector species, leading to (ii) its transmission to subsequent generations, (iii) its increase in frequency and spread in target mosquito populations, (iv) its simultaneous propagation of a linked genetic trait aimed at reducing vectorial capacity for Plasmodium, and (v) reduced vectorial capacity for parasites in target mosquito populations as the gene drive system reaches fixation in target mosquito populations, causing (vi) decreased malaria incidence and prevalence. Here the scope, objectives, trial design elements, and approaches to monitoring for initial field releases of such gene dive systems are considered, informed by the successful implementation of field trials of biological control agents, as well as other vector control tools, including insecticides, Wolbachia, larvicides, and attractive-toxic sugar bait systems. Specific research questions to be addressed in initial gene drive field trials are identified, and adaptive trial design is explored as a potentially constructive and flexible approach to facilitate testing of the causal pathway. A fundamental question for decision-makers for the first field trials will be whether there should be a selective focus on earlier points of the pathway, such as genetic efficacy via measurement of the increase in frequency and spread of the gene drive system in target populations, or on wider interrogation of the entire pathway including entomological and epidemiological efficacy. How and when epidemiological efficacy will eventually be assessed will be an essential consideration before decisions on any field trial protocols are finalized and implemented, regardless of whether initial field trials focus exclusively on the measurement of genetic efficacy, or on broader aspects of the causal pathway. Statistical and modelling tools are currently under active development and will inform such decisions on initial trial design, locations, and endpoints. Collectively, the considerations here advance the realization of developer ambitions for the first field trials of low-threshold gene drive for malaria vector control within the next 5 years.

Jordan reported [approximately equal to] 1.1 million confirmed COVID-19 cases and [approximately equal to] 12,500 deaths by the end of December 2021 (1), accounting for [approximately equal to] 6.0% of [...]

As malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low‐prevalence areas are increasingly needed. For low‐burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons. However, in areas with both routine surveillance data and prevalence surveys, models that make use of the spatial information from prevalence point‐surveys might make more accurate predictions. Using case studies in Indonesia, Senegal and Madagascar, we compare the out‐of‐sample mean absolute error for two methods for incorporating point‐level, spatial information into disaggregation regression models. The first simply fits a binomial‐likelihood, logit‐link, Gaussian random field to prevalence point‐surveys to create a new covariate. The second is a multi‐likelihood model that is fitted jointly to prevalence point‐surveys and polygon incidence data. We find that in most cases there is no difference in mean absolute error between models. In only one case, did the new models perform the best. More generally, our results demonstrate that combining these types of data has the potential to reduce absolute error in estimates of malaria incidence but that simpler baseline models should always be fitted as a benchmark. [ABSTRACT FROM AUTHOR]

Abstract Background Control of mosquitoes that transmit malaria has been the mainstay in the fight against the disease, but alternative methods are required in view of emerging insecticide resistance. Entomopathogenic fungi are candidate alternatives, but to date, few trials have translated the use of these agents to field-based evaluations of their actual impact on mosquito survival and malaria risk. Mineral oil-formulations of the entomopathogenic fungi Metarhizium anisopliae and Beauveria bassiana were applied using five different techniques that each exploited the behaviour of malaria mosquitoes when entering, host-seeking or resting in experimental huts in a malaria endemic area of rural Tanzania. Results Survival of mosquitoes was reduced by 39-57% relative to controls after forcing upward house-entry of mosquitoes through fungus treated baffles attached to the eaves or after application of fungus-treated surfaces around an occupied bed net (bed net strip design). Moreover, 68 to 76% of the treatment mosquitoes showed fungal growth and thus had sufficient contact with fungus treated surfaces. A population dynamic model of malaria-mosquito interactions shows that these infection rates reduce malaria transmission by 75-80% due to the effect of fungal infection on adult mortality alone. The model also demonstrated that even if a high proportion of the mosquitoes exhibits outdoor biting behaviour, malaria transmission was still significantly reduced. Conclusions Entomopathogenic fungi strongly affect mosquito survival and have a high predicted impact on malaria transmission. These entomopathogens represent a viable alternative for malaria control, especially if they are used as part of an integrated vector management strategy.

Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations of resistance phenotypes in field populations. We use 6,423 observations of the prevalence of resistance to the most important vector control insecticides to inform a Bayesian geostatistical ensemble modelling approach, generating fine-scale predictive maps of resistance phenotypes in mosquitoes from the Anopheles gambiae complex across Africa. Our models are informed by a suite of 111 predictor variables describing potential drivers of selection for resistance. Our maps show alarming increases in the prevalence of resistance to pyrethroids and DDT across sub-Saharan Africa from 2005 to 2017, with mean mortality following insecticide exposure declining from almost 100% to less than 30% in some areas, as well as substantial spatial variation in resistance trends. Malaria control efforts are threatened by the emergence of insecticide resistance in mosquito vector populations. This study provides fine-resolution maps of insecticide resistance levels in malaria vectors for large parts of Sub-Saharan Africa; the maps quantify recent spatial trends in resistance and can assist in the implementation of resistance management practices. [ABSTRACT FROM AUTHOR]

A promising strategy for reducing the transmission of dengue and other arboviral human diseases by Aedes aegypti mosquito vector populations involves field introductions of the endosymbiotic bacteria Wolbachia. Wolbachia infections inhibit viral transmission by the mosquito, and can spread between mosquito hosts to reach high frequencies in the vector population. Wolbachia spreads by maternal transmission, and spread dynamics can be variable and highly dependent on natural mosquito population dynamics, population structure and fitness components.We develop a mathematical model of an A. aegypti metapopulation that incorporates empirically validated relationships describing density‐dependent mosquito fitness components. We assume that density dependent relationships differ across subpopulations, and construct heterogeneous landscapes for which model‐predicted patterns of variation in mosquito abundance and demography approximate those observed in field populations. We then simulate Wolbachia release strategies similar to that used in field trials.We show that our model can produce rates of spatial spread of Wolbachia similar to those observed following field releases.We then investigate how different types of spatio‐temporal variation in mosquito habitat, as well as different fitness costs incurred by Wolbachia on the mosquito host, influence predicted spread rates. We find that fitness costs reduce spread rates more strongly when the habitat landscape varies temporally due to stochastic and seasonal processes.Synthesis and applications: Our empirically based modelling approach represents effects of environmental heterogeneity on the spatial spread of Wolbachia. The models can assist in interpreting observed spread patterns following field releases and in designing suitable release strategies for targeting spatially heterogeneous vector populations. Our empirically based modelling approach represents effects of environmental heterogeneity on the spatial spread of Wolbachia. The models can assist in interpreting observed spread patterns following field releases and in designing suitable release strategies for targeting spatially heterogeneous vector populations. [ABSTRACT FROM AUTHOR]

Background: Arbovirus transmission by the mosquito Aedes aegypti can be reduced by the introduction and establishment of the endosymbiotic bacteria Wolbachia in wild populations of the vector. Wolbachia spreads by increasing the fitness of its hosts relative to uninfected mosquitoes. However, mosquito fitness is also strongly affected by population size through density-dependent competition for limited food resources. We do not understand how this natural variation in fitness affects symbiont spread, which limits our ability to design successful control strategies. Results: We develop a mathematical model to predict A. aegypti-Wolbachia dynamics that incorporates larval density-dependent variation in important fitness components of infected and uninfected mosquitoes. Our model explains detailed features of the mosquito-Wolbachia dynamics observed in two independent experimental A. aegypti populations, allowing the combined effects on dynamics of multiple density-dependent fitness components to be characterized. We apply our model to investigate Wolbachia field release dynamics, and show how invasion outcomes can depend strongly on the severity of density-dependent competition at the release site. Specifically, the ratio of released relative to wild mosquitoes required to attain a target infection frequency (at the end of a release program) can vary by nearly an order of magnitude. The time taken for Wolbachia to become established following releases can differ by over 2 years. These effects depend on the relative fitness of field and insectaryreared mosquitoes. Conclusions: Models of Wolbachia invasion incorporating density-dependent demographic variation in the host population explain observed dynamics in experimental A. aegypti populations. These models predict strong effects of density-dependence on Wolbachia dynamics in field populations, and can assist in the effective use of Wolbachia to control the transmission of arboviruses such as dengue, chikungunya and zika. [ABSTRACT FROM AUTHOR]

Prediction and control of the spread of infectious disease in human populations benefits greatly from our growing capacity to quantify human movement behavior. Here we develop a mathematical model for non-transmissible infections contracted from a localized environmental source, informed by a detailed description of movement patterns of the population of Great Britain. The model is applied to outbreaks of Legionnaires' disease, a potentially life-threatening form of pneumonia caused by the bacteria Legionella pneumophilia. We use case-report data from three recent outbreaks that have occurred in Great Britain where the source has already been identified by public health agencies. We first demonstrate that the amount of individual-level heterogeneity incorporated in the movement data greatly influences our ability to predict the source location. The most accurate predictions were obtained using reported travel histories to describe movements of infected individuals, but using detailed simulation models to estimate movement patterns offers an effective fast alternative. Secondly, once the source is identified, we show that our model can be used to accurately determine the population likely to have been exposed to the pathogen, and hence predict the residential locations of infected individuals. The results give rise to an effective control strategy that can be implemented rapidly in response to an outbreak. [ABSTRACT FROM AUTHOR]

Certain strains of the endosymbiont Wolbachia have the potential to lower the vectorial capacity of mosquito populations and assist in controlling a number of mosquito-borne diseases. An important consideration when introducing Wolbachia-carrying mosquitoes into natural populations is the minimisation of any transient increase in disease risk or biting nuisance. This may be achieved by predominantly releasing male mosquitoes. To explore this, we use a sex-structured model of Wolbachia-mosquito interactions. We first show that Wolbachia spread can be initiated with very few infected females provided the infection frequency in males exceeds a threshold. We then consider realistic introduction scenarios involving the release of batches of infected mosquitoes, incorporating seasonal fluctuations in population size. For a range of assumptions about mosquito population dynamics we find that male-biased releases allow the infection to spread after the introduction of low numbers of females, many fewer than with equal sex-ratio releases. We extend the model to estimate the transmission rate of a mosquito-borne pathogen over the course of Wolbachia establishment. For a range of release strategies we demonstrate that male-biased release of Wolbachia-infected mosquitoes can cause substantial transmission reductions without transiently increasing disease risk. The results show the importance of including mosquito population dynamics in studying Wolbachia spread and that male-biased releases can be an effective and safe way of rapidly establishing the symbiont in mosquito populations. Author Summary: Wolbachia are symbiotic bacteria that are found in many insect species. Recent laboratory studies show that certain strains of Wolbachia can reduce the capacity of mosquito species to transmit diseases such as dengue fever and malaria, either by directly inhibiting the pathogen or by shortening lifespan. However, little is known about how easily these bacteria will spread in natural mosquito populations or the impact of deliberate Wolbachia introduction on disease transmission. We use a simple model of Wolbachia-mosquito interactions to explore the design of field releases of infected mosquitoes to initiate symbiont spread. A particular concern is how Wolbachia can be introduced while releasing only small numbers of female mosquitoes which may bite humans and transmit disease. The models include explicit mosquito population dynamics including seasonal fluctuations in population size and different forms of population regulation. We find that rapid Wolbachia establishment is possible by releasing predominantly male mosquitoes, though the number of insects introduced may need to be large. This strategy requires the introduction of considerably fewer females compared to equal sex-ratio releases and is unlikely to increase disease transmission throughout the intervention. We demonstrate that once Wolbachia has become established, substantial reductions in disease transmission are possible. [ABSTRACT FROM AUTHOR]

In developing strategies to control malaria vectors, there is increased interest in biological methods that do not cause instant vector mortality, but have sublethal and lethal effects at different ages and stages in the mosquito life cycle. These techniques, particularly if integrated with other vector control interventions, may produce substantial reductions in malaria transmission due to the total effect of alterations to multiple life history parameters at relevant points in the life-cycle and transmission-cycle of the vector. To quantify this effect, an analytically tractable gonotrophic cycle model of mosquito-malaria interactions is developed that unites existing continuous and discrete feeding cycle approaches. As a case study, the combined use of fungal biopesticides and insecticide treated bednets (ITNs) is considered. Low values of the equilibrium EIR and human prevalence were obtained when fungal biopesticides and ITNs were combined, even for scenarios where each intervention acting alone had relatively little impact. The effect of the combined interventions on the equilibrium EIR was at least as strong as the multiplicative effect of both interventions. For scenarios representing difficult conditions for malaria control, due to high transmission intensity and widespread insecticide resistance, the effect of the combined interventions on the equilibrium EIR was greater than the multiplicative effect, as a result of synergistic interactions between the interventions. Fungal biopesticide application was found to be most effective when ITN coverage was high, producing significant reductions in equilibrium prevalence for low levels of biopesticide coverage. By incorporating biological mechanisms relevant to vectorial capacity, continuous-time vector population models can increase their applicability to integrated vector management. [ABSTRACT FROM AUTHOR]

Abstract: We develop a simple individual-based model to gain an understanding of the drivers of aggregation behaviour in nomadic foragers. The model incorporates two key elements influencing nomadic foragers in variable environments: uncertainty regarding the location of food sources and variability in the spatio-temporal distribution of ephemeral food sources. A genetic algorithm is used to evolve parameters describing an individual''s movement and aggregation strategy. We apply the aggregation model to a case study of the Bornean bearded pig (Sus barbatus). Bearded pigs are ideal for considering the foraging advantages of aggregation, because they are highly mobile and exhibit a variety of aggregation strategies, ranging from solitary and sedentary to mass aggregation and wide ranging migration. Our model demonstrates the “many-wrongs principle”, and shows that environmental variability, uncertainty in the location of food sources, and local population density drive aggregation behaviour. [Copyright &y& Elsevier]

Early on in the COVID-19 pandemic, the WHO Eastern Mediterranean Regional Office recognised the importance of epidemiological modelling to forecast the progression of the COVID-19 pandemic to support decisions guiding the implementation of response measures. We established a modelling support team to facilitate the application of epidemiological modelling analyses in the Eastern Mediterranean Region (EMR) countries. Here, we present an innovative, stepwise approach to participatory modelling of the COVID-19 pandemic that engaged decision-makers and public health professionals from countries throughout all stages of the modelling process. Our approach consisted of first identifying the relevant policy questions, collecting country-specific data and interpreting model findings from a decision-maker's perspective, as well as communicating model uncertainty. We used a simple modelling methodology that was adaptable to the shortage of epidemiological data, and the limited modelling capacity, in our region. We discuss the benefits of using models to produce rapid decision-making guidance for COVID-19 control in the WHO EMR, as well as challenges that we have experienced regarding conveying uncertainty associated with model results, synthesising and comparing results across multiple modelling approaches, and modelling fragile and conflict-affected states., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The endosymbiont Wolbachia infects a large number of insect species and is capable of rapid spread when introduced into a novel host population. The bacteria spread by manipulating their hosts' reproduction, and their dynamics are influenced by the demographic structure of the host population and patterns of contact between individuals. Reaction-diffusion models of the spatial spread of Wolbachia provide a simple analytical description of their spatial dynamics but do not account for significant details of host population dynamics. We develop a metapopulation model describing the spatial dynamics of Wolbachia in an age-structured host insect population regulated by juvenile density-dependent competition. The model produces similar dynamics to the reaction-diffusion model in the limiting case where the host's habitat quality is spatially homogeneous and Wolbachia has a small effect on host fitness. When habitat quality varies spatially, Wolbachia spread is usually much slower, and the conditions necessary for local invasion are strongly affected by immigration of insects from surrounding regions. Spread is most difficult when variation in habitat quality is spatially correlated. The results show that spatial variation in the density-dependent competition experienced by juvenile host insects can strongly affect the spread of Wolbachia infections, which is important to the use of Wolbachia to control insect vectors of human disease and other pests.