Heterogeneity,Mixing, and the Spatial Scales of Mosquito-Borne Pathogen Transmission

The Ross-Macdonald model has dominated theory for mosquito-borne pathogen transmission dynamics and control for over a century. The model, like many other basic population models, makes the mathematically convenient assumption that populations are well mixed; i.e., that each mosquito is equally likely to bite any vertebrate host. This assumption raises questions about the validity and utility of current theory because it is in conflict with preponderant empirical evidence that transmission is heterogeneous. Here, we propose a new dynamic framework that is realistic enough to describe biological causes of heterogeneous transmission of mosquito-borne pathogens of humans, yet tractable enough to provide a basis for developing and improving general theory. The framework is based on the ecological context of mosquito blood meals and the fine-scale movements of individual mosquitoes and human hosts that give rise to heterogeneous transmission. Using this framework, we describe pathogen dispersion in terms of individual-level analogues of two classical quantities: vectorial capacity and the basic reproductive number, . Importantly, this framework explicitly accounts for three key components of overall heterogeneity in transmission: heterogeneous exposure, poor mixing, and finite host numbers. Using these tools, we propose two ways of characterizing the spatial scales of transmission—pathogen dispersion kernels and the evenness of mixing across scales of aggregation—and demonstrate the consequences of a model''s choice of spatial scale for epidemic dynamics and for estimation of , both by a priori model formulas and by inference of the force of infection from time-series data.     

Malaria Drug Resistance: The Impact of Human Movement and Spatial Heterogeneity

Human habitat connectivity, movement rates, and spatial heterogeneity have tremendous impact on malaria transmission. In this paper, a deterministic system of differential equations for malaria transmission incorporating human movements and the development of drug resistance malaria in an \(n\) patch system is presented. The disease-free equilibrium of the model is globally asymptotically stable when the associated reproduction number is less than unity. For a two patch case, the boundary equilibria (drug sensitive-only and drug resistance-only boundary equilibria) when there is no movement between the patches are shown to be locally asymptotically stable when they exist; the co-existence equilibrium is locally asymptotically stable whenever the reproduction number for the drug sensitive malaria is greater than the reproduction number for the resistance malaria. Furthermore, numerical simulations of the connected two patch model (when there is movement between the patches) suggest that co-existence or competitive exclusion of the two strains can occur when the respective reproduction numbers of the two strains exceed unity. With slow movement (or low migration) between the patches, the drug sensitive strain dominates the drug resistance strain. However, with fast movement (or high migration) between the patches, the drug resistance strain dominates the drug sensitive strain.     

Malaria Infection Has Spatial,Temporal, and Spatiotemporal Heterogeneity in Unstable Malaria Transmission Areas in Northwest Ethiopia

Background

Malaria elimination requires successful nationwide control efforts. Detecting the spatiotemporal distribution and mapping high-risk areas are useful to effectively target pockets of malaria endemic regions for interventions.

Objective

The aim of the study was to identify patterns of malaria distribution by space and time in unstable malaria transmission areas in northwest Ethiopia.

Methods

Data were retrieved from the monthly reports stored in the district malaria offices for the period between 2003 and 2012. Eighteen districts in the highland and fringe malaria areas were included and geo-coded for the purpose of this study. The spatial data were created in ArcGIS10 for each district. The Poisson model was used by applying Kulldorff methods using the SaTScan™ software to analyze the purely temporal, spatial and space-time clusters of malaria at a district levels.

Results

The study revealed that malaria case distribution has spatial, temporal, and spatiotemporal heterogeneity in unstable transmission areas. Most likely spatial malaria clusters were detected at Dera, Fogera, Farta, Libokemkem and Misrak Este districts (LLR =197764.1, p<0.001). Significant spatiotemporal malaria clusters were detected at Dera, Fogera, Farta, Libokemkem and Misrak Este districts (LLR=197764.1, p<0.001) between 2003/1/1 and 2012/12/31. A temporal scan statistics identified two high risk periods from 2009/1/1 to 2010/12/31 (LLR=72490.5, p<0.001) and from 2003/1/1 to 2005/12/31 (LLR=26988.7, p<0.001).

Conclusion

In unstable malaria transmission areas, detecting and considering the spatiotemporal heterogeneity would be useful to strengthen malaria control efforts and ultimately achieve elimination.     

The Importance of Age Dependent Mortality and the Extrinsic Incubation Period in Models of Mosquito-Borne Disease Transmission and Control

Nearly all mathematical models of vector-borne diseases have assumed that vectors die at constant rates. However, recent empirical research suggests that mosquito mortality rates are frequently age dependent. This work develops a simple mathematical model to assess how relaxing the classical assumption of constant mortality affects the predicted effectiveness of anti-vectorial interventions. The effectiveness of mosquito control when mosquitoes die at age dependent rates was also compared across different extrinsic incubation periods. Compared to a more realistic age dependent model, constant mortality models overestimated the sensitivity of disease transmission to interventions that reduce mosquito survival. Interventions that reduce mosquito survival were also found to be slightly less effective when implemented in systems with shorter EIPs. Future transmission models that examine anti-vectorial interventions should incorporate realistic age dependent mortality rates.     

School-Based Countrywide Seroprevalence Survey Reveals Spatial Heterogeneity in Malaria Transmission in the Gambia

Background

As the geographical distribution of malaria transmission becomes progressively clustered, identifying residual pockets of transmission is important for research and for targeting interventions. Malarial antibody-based surveillance is increasingly recognised as a valuable complement to classic methods for the detection of infection foci especially at low transmission levels. The study presents serological evidence for transmission heterogeneity among school children in The Gambia measured during the dry, non-transmission season.

Methods

Healthy primary school children were randomly selected from 30 schools across the country and screened for malaria infection (microscopy) and antimalarial antibodies (MSP1₁₉). Antibody distribution was modelled using 2-component finite mixture model with cut-off for positivity from pooled sera set at 2-standard deviation from the mean of the first component. Factors associated with a positive serological status were identified in a univariate model and then combined in a multilevel mixed-effects logistic regression model, simultaneously adjusting for variations between individuals and school.

Results

A total of 4140 children, 1897 (46%) boys, were enrolled with mean age of 10.2 years (SD 2.6, range 4–20 years). Microscopy results available for 3640 (87.9%) children showed that 1.9% (69) were positive for Plasmodium falciparum infections, most of them (97.1%, 67/69) asymptomatic. The overall seroprevalence was 12.7% (527/4140) with values for the schools ranging from 0.6% to 43.8%. Age (OR 1.12, 95% CI 1.07–1.16,) and parasite carriage (OR 3.36, 95% CI 1.95–5.79) were strongly associated with seropositivity.

Conclusion

Serological responses to malaria parasites could identify individuals who were or had been infected, and clusters of residual transmission. Field-adapted antibody tests able to guide mass screening and treatment campaigns would be extremely useful.     

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations.     

Spatial Variation in an Avian Host Community: Implications for Disease Dynamics

Because many pathogens can infect multiple host species within a community, disease dynamics in a focal host species can be affected by the composition of the host community. We examine the extent to which spatial variation in species’ abundances in an avian host community may contribute to geographically varying prevalence of a recently emerged wildlife pathogen. Mycoplasma gallisepticum is a pathogen novel to songbirds that has caused substantial mortality in house finches (Carpodacus mexicanus) in eastern North America. Though the house finch is the primary host species for M. gallisepticum, the American goldfinch (Spinus tristis) and northern cardinal (Cardinalis cardinalis) are alternate hosts, and laboratory experiments have demonstrated M. gallisepticum transmission between house finches and goldfinches. Still unknown is the real world impact on disease dynamics of variation in abundances of the three hosts. We analyzed data from winter-long bird and disease surveys in the northeastern United States. We found that higher disease prevalence in house finches was associated with higher numbers of northern cardinals and American goldfinches, although only the effect of cardinal abundance was statistically significant. Nevertheless, our results indicate that spatial variation in bird communities has the potential to cause geographic variation in disease prevalence in house finches.     

人口流动性对感染性疾病扩散与传播的影响

研究人口流动性对具有斑快结构的感染性疾病传播与扩散的影响,讨论了具有斑块结构感染性疾病SIS模型的全局稳定性,得到了该模型基本再生数的倍增效应．     

Temporal Variability and Social Heterogeneity in Disease Transmission: The Case of SARS in Hong Kong

The extent to which self-adopted or intervention-related changes in behaviors affect the course of epidemics remains a key issue for outbreak control. This study attempted to quantify the effect of such changes on the risk of infection in different settings, i.e., the community and hospitals. The 2002–2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong, where 27% of cases were healthcare workers, was used as an example. A stochastic compartmental SEIR (susceptible-exposed-infectious-removed) model was used: the population was split into healthcare workers, hospitalized people and general population. Super spreading events (SSEs) were taken into account in the model. The temporal evolutions of the daily effective contact rates in the community and hospitals were modeled with smooth functions. Data augmentation techniques and Markov chain Monte Carlo (MCMC) methods were applied to estimate SARS epidemiological parameters. In particular, estimates of daily reproduction numbers were provided for each subpopulation. The average duration of the SARS infectious period was estimated to be 9.3 days (±0.3 days). The model was able to disentangle the impact of the two SSEs from background transmission rates. The effective contact rates, which were estimated on a daily basis, decreased with time, reaching zero inside hospitals. This observation suggests that public health measures and possible changes in individual behaviors effectively reduced transmission, especially in hospitals. The temporal patterns of reproduction numbers were similar for healthcare workers and the general population, indicating that on average, an infectious healthcare worker did not infect more people than any other infectious person. We provide a general method to estimate time dependence of parameters in structured epidemic models, which enables investigation of the impact of control measures and behavioral changes in different settings.     

Bacterial Activity, Community Structure, and Centimeter-Scale Spatial Heterogeneity in Contaminated Soil

In an anthropogenically disturbed soil (88% sand, 8% silt, 4% clay), 150-mg samples were studied to examine the fine-scale relationship of bacterial activity and community structure to heavy metal contaminants. The soils had been contaminated for over 40 years with aromatic solvents, Pb, and Cr. Samples from distances of <1, 5, 15, and 50 cm over a depth range of 40–90 cm underwent a sequential analysis to determine metabolic potential (from ¹⁴C glucose mineralization), bacterial community structure [using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE)], and total extractable Pb and Cr levels. Metabolic potential varied by as much as 10,000-fold in samples <1 cm apart; log–log plots of metal concentration and microbial metabolic potential showed no correlation with each other. Overall, metal concentrations ranged from 9 to 29,000 mg kg⁻¹ for Pb and from 3 to 8500 mg kg⁻¹ for Cr with small zones of high contamination present. All regions exhibited variable metal concentrations, with some soil samples having 30-fold differences in metal concentration in sites <1 cm apart. Geostatistical analysis revealed a strong spatial dependence for all three parameters tested (metabolic activity, Pb, and Cr levels) with a range up to 30 cm. Kriging maps showed that in zones of high metal, the corresponding metabolic activity was low suggesting that metals negatively impacted the microbial community. PCR-DGGE analysis revealed that diverse communities were present in the soils with a random distribution of phylotypes throughout the sampling zones. These results suggest the presence of spatially isolated microbial communities within the soil profile.     

Coping with Spatial Heterogeneity and Temporal Variability in Resources and Risks: Adaptive Movement Behaviour by a Large Grazing Herbivore

Movement is a key mean for mobile species to cope with heterogeneous environments. While in herbivorous mammals large-scale migration has been widely investigated, fine-scale movement responses to local variations in resources and predation risk remain much less studied, especially in savannah environments. We developed a novel approach based on complementary movement metrics (residence time, frequency of visits and regularity of visits) to relate movement patterns of a savannah grazer, the blue wildebeest Connochaetes taurinus, to fine-scale variations in food availability, predation risk and water availability in the Kruger National Park, South Africa. Wildebeests spent more time in grazing lawns where the grass is of higher quality but shorter than in seep zones, where the grass is of lower quality but more abundant. Although the daily distances moved were longer during the wet season compared to the dry season, the daily net displacement was lower, and the residence time higher, indicating a more frequent occurrence of area-concentred searching. In contrast, during the late dry season the foraging sessions were more fragmented and wildebeests moved more frequently between foraging areas. Surprisingly, predation risk appeared to be the second factor, after water availability, influencing movement during the dry season, when resources are limiting and thus expected to influence movement more. Our approach, using complementary analyses of different movement metrics, provided an integrated view of changes in individual movement with varying environmental conditions and predation risk. It makes it possible to highlight the adaptive behavioral decisions made by wildebeest to cope with unpredictable environmental variations and provides insights for population conservation.     

Modeling the Circulation of a Disease Between Two Host Populations on non Coincident Spatial Domains

We derive a reaction–diffusion system modeling the spatial propagation of a disease with kinetics occurring on distinct spatial domains. This corresponds to the actual invasion of a disease from a species living in a given spatial domain toward a second species living in a different spatial domain. We study the global existence of solutions and discuss the long time behavior of solutions. Then we consider a special case, based on a model of brain worm infection from white-tailed deer to moose populations, for which we discuss the invasion success/failure process and disprove a conjecture stated in an earlier work.     

Comparative Host Feeding Patterns of the Asian Tiger Mosquito,Aedes albopictus,in Urban and Suburban Northeastern USA and Implications for Disease Transmission

Background

Aedes albopictus is an invasive species which continues expanding its geographic range and involvement in mosquito-borne diseases such as chikungunya and dengue. Host selection patterns by invasive mosquitoes are critically important because they increase endemic disease transmission and drive outbreaks of exotic pathogens. Traditionally, Ae. albopictus has been characterized as an opportunistic feeder, primarily feeding on mammalian hosts but occasionally acquiring blood from avian sources as well. However, limited information is available on their feeding patterns in temperate regions of their expanded range. Because of the increasing expansion and abundance of Ae. albopictus and the escalating diagnoses of exotic pathogens in travelers returning from endemic areas, we investigated the host feeding patterns of this species in newly invaded areas to further shed light on its role in disease ecology and assess the public health threat of an exotic arbovirus outbreak.

Methodology/Principal Findings

We identified the vertebrate source of 165 blood meals in Ae. albopictus collected between 2008 and 2011 from urban and suburban areas in northeastern USA. We used a network of Biogents Sentinel traps, which enhance Ae. albopictus capture counts, to conduct our collections of blooded mosquitoes. We also analyzed blooded Culex mosquitoes collected alongside Ae. albopictus in order to examine the composition of the community of blood sources. We found no evidence of bias since as expected Culex blood meals were predominantly from birds (n = 149, 93.7%) with only a small proportion feeding on mammals (n = 10, 6.3%). In contrast, Aedes albopictus fed exclusively on mammalian hosts with over 90% of their blood meals derived from humans (n = 96, 58.2%) and domesticated pets (n = 38, 23.0% cats; and n = 24, 14.6% dogs). Aedes albopictus fed from humans significantly more often in suburban than in urban areas (χ², p = 0.004) and cat-derived blood meals were greater in urban habitats (χ², p = 0.022). Avian-derived blood meals were not detected in any of the Ae. albopictus tested.

Conclusions/Significance

The high mammalian affinity of Ae. albopictus suggests that this species will be an efficient vector of mammal- and human-driven zoonoses such as La Crosse, dengue, and chikungunya viruses. The lack of blood meals obtained from birds by Ae. albopictus suggest that this species may have limited exposure to endemic avian zoonoses such as St. Louis encephalitis and West Nile virus, which already circulate in the USA. However, growing populations of Ae. albopictus in major metropolitan urban and suburban centers, make a large autochthonous outbreak of an arbovirus such as chikungunya or dengue viruses a clear and present danger. Given the difficulties of Ae. albopictus suppression, we recommend that public health practitioners and policy makers install proactive measures for the imminent mitigation of an exotic pathogen outbreak.     

Movement Behavior and Host Location Ability of Corythucha ciliata

Insect movement behavior is highly important in entomological population ecology, behavioral ecology and conservation, and in invasion ecology. In this study, we used an exotic lace bug (Corythucha ciliata) as a model organism to address the hypothesis that an insect species invading a new area has a high host location ability and rapid mobility by which it can be successfully carried to a new habitat. To test this hypothesis, three movement parameters (speed, duration and distance) of C. ciliata were assessed using laboratory and field observations. We found that 5^th-instar nymphs of C. ciliata could move as far as 750 cm throughout their lifespan and that they moved an average of 0.038 m/min during the first 15 minutes after release, which was significantly farther than that of other instars. Of the tested nymphs, 21.85% could locate their host trees; of adults released 20 m from hosts, 11% reached the host trees on the first day, with an average flight distance of 22.14 m and a maximum flight distance of 27 m. The results of this study partly explain the mechanism of rapid diffusion. These results are also important for predicting population spread, improving eradication surveys, and managing future introductions of C. ciliata.