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AbstractInfectious disease dynamics operate across biological scales: pathogens replicate within hosts but transmit among populations. Functional changes in the pathogen-host interaction thus generate cascading effects across organizational scales. We investigated within-host dynamics and among-host transmission of three strains (SAT-1, -2, -3) of foot-and-mouth disease viruses (FMDVs) in their wildlife host, African buffalo. We combined data on viral dynamics and host immune responses with mathematical models to ask the following questions: How do viral and immune dynamics vary among strains? Which viral and immune parameters determine viral fitness within hosts? And how do within-host dynamics relate to virus transmission? Our data reveal contrasting within-host dynamics among viral strains, with SAT-2 eliciting more rapid and effective immune responses than SAT-1 and SAT-3. Within-host viral fitness was overwhelmingly determined by variation among hosts in immune response activation rates but not by variation among individual hosts in viral growth rate. Our analyses investigating across-scale linkages indicate that viral replication rate in the host correlates with transmission rates among buffalo and that adaptive immune activation rate determines the infectious period. These parameters define the virus's relative basic reproductive number (ℛ 0 ), suggesting that viral invasion potential may be predictable from within-host dynamics.

African horse sickness is an equine orbivirus transmitted by Culicoides Latreille biting midges. In the last 80 years, it has caused several devastating outbreaks in the equine population in Europe, the Far and Middle East, North Africa, South-East Asia, and sub-Saharan Africa. The disease is endemic in South Africa; however, a unique control area has been set up in the Western Cape where increased surveillance and control measures have been put in place. A deterministic metapopulation model was developed to explore if an outbreak might occur, and how it might develop, if a latently infected horse was to be imported into the control area, by varying the geographical location and months of import. To do this, a previously published ordinary differential equation model was developed with a metapopulation approach and included a vaccinated horse population. Outbreak length, time to peak infection, number of infected horses at the peak, number of horses overall affected (recovered or dead), re-emergence, and Rv (the basic reproduction number in the presence of vaccination) were recorded and displayed using GIS mapping. The model predictions were compared to previous outbreak data to ensure validity. The warmer months (November to March) had longer outbreaks than the colder months (May to September), took more time to reach the peak, and had a greater total outbreak size with more horses infected at the peak. Rv appeared to be a poor predictor of outbreak dynamics for this simulation. A sensitivity analysis indicated that control measures such as vaccination and vector control are potentially effective to manage the spread of an outbreak, and shortening the vaccination window to July to September may reduce the risk of vaccine-associated outbreaks., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 de Klerk et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Many infectious pathogens are shared through social interactions, and examining host connectivity has offered valuable insights for understanding patterns of pathogen transmission across wildlife species. African buffalo are social ungulates and important reservoirs of directly-transmitted pathogens that impact numerous wildlife and livestock species. Here, we analyzed African buffalo social networks to quantify variation in close contacts, examined drivers of contact heterogeneity, and investigated how the observed contact patterns affect pathogen invasion likelihoods for a wild social ungulate. We collected continuous association data using proximity collars and sampled host traits approximately every 2 months during a 15-month study period in Kruger National Park, South Africa. Although the observed herd was well connected, with most individuals contacting each other during each bimonthly interval, our analyses revealed striking heterogeneity in close-contact associations among herd members. Network analysis showed that individual connectivity was stable over time and that individual age, sex, reproductive status, and pairwise genetic relatedness were important predictors of buffalo connectivity. Calves were the most connected members of the herd, and adult males were the least connected. These findings highlight the role susceptible calves may play in the transmission of pathogens within the herd. We also demonstrate that, at time scales relevant to infectious pathogens found in nature, the observed level of connectivity affects pathogen invasion likelihoods for a wide range of infectious periods and transmissibilities. Ultimately, our study identifies key predictors of social connectivity in a social ungulate and illustrates how contact heterogeneity, even within a highly connected herd, can shape pathogen invasion likelihoods., Competing Interests: The authors have no conflicts of interest to declare., (© 2023 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Transboundary livestock diseases are a high priority for policy makers because of the serious economic burdens associated with infection. In order to make well informed preparedness and response plans, policy makers often utilize mathematical models to understand possible outcomes of different control strategies and outbreak scenarios. Many of these models focus on the transmission between herds and the overall trajectory of the outbreak. While the course of infection within herds has not been the focus of the majority of models, a thorough understanding of within-herd dynamics can provide valuable insight into a disease system by providing information on herd-level biological properties of the infection, which can be used to inform decision making in both endemic and outbreak settings and to inform larger between-herd models. In this study, we develop three stochastic simulation models to study within-herd foot and mouth disease dynamics and the implications of different empirical data-based assumptions about the timing of the onset of infectiousness and clinical signs. We also study the influence of herd size and the proportion of the herd that is initially infected on the outcome of the infection. We find that increasing herd size increases the duration of infectiousness and that the size of the herd plays a more significant role in determining this duration than the number of initially infected cattle in that herd. We also find that the assumptions made regarding the onset of infectiousness and clinical signs, which are based on contradictory empirical findings, can result in the predictions about when infection would be detectable differing by several days. Therefore, the disease progression used to characterize the course of infection in a single bovine host could have significant implications for determining when herds can be detected and subsequently controlled; the timing of which could influence the overall predicted trajectory of outbreaks., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

The prevalence and distribution of African alphaviruses such as chikungunya have increased in recent years. Therefore, a better understanding of the local distribution of alphaviruses in vectors across the African continent is important. Here, entomological surveillance was performed from 2014 to 2018 at selected sites in north-eastern parts of South Africa where alphaviruses have been identified during outbreaks in humans and animals in the past. Mosquitoes were collected using a net, CDC-light, and BG-traps. An alphavirus genus-specific nested RT-PCR was used for screening, and positive pools were confirmed by sequencing and phylogenetic analysis. We collected 64,603 mosquitoes from 11 genera, of which 39,035 females were tested. Overall, 1462 mosquito pools were tested, of which 21 were positive for alphaviruses. Sindbis (61.9%, N = 13) and Middelburg (28.6%, N = 6) viruses were the most prevalent. Ndumu virus was detected in two pools (9.5%, N = 2). No chikungunya positive pools were identified. Arboviral activity was concentrated in peri-urban, rural, and conservation areas. A range of Culicidae species, including Culex univittatus , Cx. pipiens s.l., Aedes durbanensis , and the Ae. dentatus group, were identified as potential vectors. These findings confirm the active circulation and distribution of alphaviruses in regions where human or animal infections were identified in South Africa.

Mathematical models of vector-borne infections, including malaria, often assume age-independent mortality rates of vectors, despite evidence that many insects senesce. In this study we present survival data on insecticide-resistant Anopheles gambiae s.l. from experiments in Côte d'Ivoire. We fit a constant mortality function and two age-dependent functions (logistic and Gompertz) to the data from mosquitoes exposed (treated) and not exposed (control) to insecticide-treated nets (ITNs), to establish biologically realistic survival functions. This enables us to explore the effects of insecticide exposure on mosquito mortality rates, and the extent to which insecticide resistance might impact the effectiveness of ITNs. We investigate this by calculating the expected number of infectious bites a mosquito will take in its lifetime, and by extension the vectorial capacity. Our results show that the predicted vectorial capacity is substantially lower in mosquitoes exposed to ITNs, despite the mosquitoes in the experiment being highly insecticide-resistant. The more realistic age-dependent functions provide a better fit to the experimental data compared to a constant mortality function and, hence, influence the predicted impact of ITNs on malaria transmission potential. In models with age-independent mortality, there is a great reduction for the vectorial capacity under exposure compared to no exposure. However, the two age-dependent functions predicted an even larger reduction due to exposure, highlighting the impact of incorporating age in the mortality rates. These results further show that multiple exposures to ITNs had a considerable effect on the vectorial capacity. Overall, the study highlights the importance of including age dependency in mathematical models of vector-borne disease transmission and in fully understanding the impact of interventions., Competing Interests: The authors have declared that no competing interests exist.

Foot-and-mouth disease (FMD) is a virulent and economically important disease of livestock, still endemic in many areas of Asia and sub-Saharan Africa. Transmission from persistently infected livestock, also known as carriers, has been proposed as a mechanism to support the persistence of FMD in endemic regions. However, whether carrier livestock can infect susceptible animals is controversial; recovered virus is infectious and there are claims of field transmission, but it remains undemonstrated experimentally. Alternate hypotheses for persistence include the movement of livestock within and between regions, and fomite contamination of the environment. Using a stochastic compartmental ordinary differential equation (ODE) model, we investigate the minimum rates of carrier transmission necessary to contribute to the maintenance of FMD in a region, and compare this to the alternate mechanism of persistence through cattle shipments. We find that carrier transmission can theoretically support persistence even at transmission rates much lower than the highest realistic rates previously proposed, and that the parameters with the most effect on the feasibility of carrier-mediated persistence are the average duration of both the carrier phase and natural immunity. However, shipment-mediated persistence remains a viable alternate mechanism for persistence without carrier transmission., (© 2021 The Authors. Transboundary and Emerging Diseases published by Wiley-VCH GmbH.)

Shuni virus is associated with neurologic and febrile illness in animals and humans. To determine potential vectors, we collected mosquitoes in South Africa and detected the virus in species of the genera Mansonia, Culex, Aedes, and Anopheles. These mosquitoes may be associated with Shuni virus outbreaks in Africa and emergence in other regions.

Mosquitoes in the Aedes and Culex genera are considered the main vectors of pathogenic flaviviruses worldwide. Entomological surveillance using universal flavivirus sets of primers in mosquitoes can detect not only pathogenic viruses but also insect-specific ones. It is hypothesized that insect-specific flaviviruses, which naturally infect these mosquitoes, may influence their vector competence for zoonotic arboviruses. Here, entomological surveillance was performed between January 2014 and May 2018 in five different provinces in the northeastern parts of South Africa, with the aim of identifying circulating flaviviruses. Mosquitoes were sampled using different carbon dioxide trap types. Overall, 64,603 adult mosquitoes were collected, which were screened by RT-PCR and sequencing. In total, 17 pools were found positive for insect-specific Flaviviruses in the mosquito genera Aedes (12/17, 70.59%) and Anopheles (5/17, 29.41%). No insect-specific viruses were detected in Culex species. Cell-fusing agent viruses were detected in Aedes aegypti and Aedes caballus . A range of anopheline mosquitoes, including Anopheles coustani , An. squamosus and An. maculipalpis , were positive for Culex flavivirus-like and Anopheles flaviviruses. These results confirm the presence of insect-specific flaviviruses in mosquito populations in South Africa, expands their geographical range and indicates potential mosquito species as vector species.

By mid-May 2020, cases of COVID-19 in the UK had been declining for over a month; a multi-phase emergence from lockdown was planned, including a scheduled partial reopening of schools on 1 June 2020. Although evidence suggests that children generally display mild symptoms, the size of the school-age population means the total impact of reopening schools is unclear. Here, we present work from mid-May 2020 that focused on the imminent opening of schools and consider what these results imply for future policy. We compared eight strategies for reopening primary and secondary schools in England. Modifying a transmission model fitted to UK SARS-CoV-2 data, we assessed how reopening schools affects contact patterns, anticipated secondary infections and the relative change in the reproduction number, R . We determined the associated public health impact and its sensitivity to changes in social distancing within the wider community. We predicted that reopening schools with half-sized classes or focused on younger children was unlikely to push R above one. Older children generally have more social contacts, so reopening secondary schools results in more cases than reopening primary schools, while reopening both could have pushed R above one in some regions. Reductions in community social distancing were found to outweigh and exacerbate any impacts of reopening. In particular, opening schools when the reproduction number R is already above one generates the largest increase in cases. Our work indicates that while any school reopening will result in increased mixing and infection amongst children and the wider population, reopening schools alone in June 2020 was unlikely to push R above one. Ultimately, reopening decisions are a difficult trade-off between epidemiological consequences and the emotional, educational and developmental needs of children. Into the future, there are difficult questions about what controls can be instigated such that schools can remain open if cases increase. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Background: There is a paucity of recent data and knowledge on mosquito diversity and potential vectors of arboviruses in South Africa, with most of the available data dating back to the 1950s-1970s. Aedes and Culex species are the major vectors of some of the principal arboviruses which have emerged and re-emerged in the past few decades., Methods: In this study we used entomological surveillance in selected areas in the north-eastern parts of South Africa from 2014 to 2018 to assess mosquito diversity, with special emphasis on the Aedes species. The impact of trap types and environmental conditions was also investigated. Identification of the blood meal sources of engorged females collected during the study period was carried out, and DNA barcodes were generated for selected species., Results: Overall, 18.5% of the total Culicidae mosquitoes collected belonged to the genus Aedes, with 14 species recognised or suspected vectors of arboviruses. Species belonging to the Neomelaniconion subgenus were commonly collected in the Bushveld savanna at conservation areas, especially Aedes mcintoshi and Aedes circumluteolus. Aedes aegypti was present in all sites, albeit in low numbers. Temperature was a limiting factor for the Aedes population, and they were almost exclusively collected at temperatures between 18 °C and 27 °C. The cytochrome oxidase subunit I (COI) barcode fragment was amplified for 21 Aedes species, and for nine of these species it was the first sequence information uploaded on GenBank., Conclusion: This study provides a better understanding of the diversity and relative abundance of Aedes species in the north-east of South Africa. The information provided here will contribute to future arboviral research and implementation of efficient vector control and prevention strategies.

Emerging diseases of wildlife origin are increasingly spilling over into humans and domestic animals. Surveillance and risk assessments for transmission between these populations are informed by a mechanistic understanding of the pathogens in wildlife reservoirs. For avian influenza viruses (AIV), much observational and experimental work in wildlife has been conducted at local scales, yet fully understanding their spread and distribution requires assessing the mechanisms acting at both local, (e.g., intrinsic epidemic dynamics), and continental scales, (e.g., long-distance migration). Here, we combined a large, continental-scale data set on low pathogenic, Type A AIV in the United States with a novel network-based application of bird banding/recovery data to investigate the migration-based drivers of AIV and their relative importance compared to well-characterized local drivers (e.g., demography, environmental persistence). We compared among regression models reflecting hypothesized ecological processes and evaluated their ability to predict AIV in space and time using within and out-of-sample validation. We found that predictors of AIV were associated with multiple mechanisms at local and continental scales. Hypotheses characterizing local epidemic dynamics were strongly supported, with age, the age-specific aggregation of migratory birds in an area and temperature being the best predictors of infection. Hypotheses defining larger, network-based features of the migration processes, such as clustering or between-cluster mixing explained less variation but were also supported. Therefore, our results support a role for local processes in driving the continental distribution of AIV., (© 2020 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of Ecological Society of America.)

Background: The rising incidence of visceral leishmaniasis due to Leishmania infantum requires novel methods to control transmission by the sand fly vector. Indoor residual spraying of insecticide (IRS) against these largely exophilic / exophagic vectors may not be the most effective method. A synthetic copy of the male sex-aggregation pheromone of the key vector species Lutzomyia longipalpis in the Americas, was co-located with residual pyrethroid insecticide, and tested for its effects on vector abundance, hence potential transmission, in a Brazilian community study., Methods: Houses within eight defined semi-urban blocks in an endemic municipality in Brazil were randomised to synthetic pheromone + insecticide or to placebo treatments. A similar number of houses located >100m from each block were placebo treated and considered as "True Controls" (thus, analysed as three trial arms). Insecticide was sprayed on a 2.6m2 surface area of the property boundary or outbuilding wall, co-located within one metre of 50mg synthetic pheromone in controlled-release dispensers. Vector numbers captured in nearby CDC light traps were recorded at monthly intervals over 3 months post intervention. Recruited sentinel houses under True Control and pheromone + insecticide treatments were similarly monitored at 7-9 day intervals. The intervention effects were estimated by mixed effects negative binomial models compared to the True Control group., Results: Dose-response field assays using 50mg of the synthetic pheromone captured a mean 4.8 (95% C.L.: 3.91, 5.80) to 6.3 (95% C.L.: 3.24, 12.11) times more vectors (female Lu. longipalpis) than using 10mg of synthetic pheromone. The intervention reduced household female vector abundance by 59% (C.L.: 48.7, 66.7%) (IRR = 0.41) estimated by the cross-sectional community study, and by 70% (C.L.: 56.7%, 78.8%) estimated by the longitudinal sentinel study. Similar reductions in male Lu. longipalpis were observed. Beneficial spill-over intervention effects were also observed at nearby untreated households with a mean reduction of 24% (95% C.L.: 0.050%, 39.8%) in female vectors. The spill-over effect in untreated houses was 44% (95% C.L.: 29.7%, 56.1%) as effective as the intervention in pheromone-treated houses. Ownership of chickens increased the intervention effects in both treated and untreated houses, attributed to the suspected synergistic attraction of the synthetic pheromone and chicken kairomones. The variation in IRR between study blocks was not associated with inter-household distances, household densities, or coverage (proportion of total households treated)., Conclusions: The study confirms the entomological efficacy of the lure-and-kill method to reduce the abundance of this important sand fly vector in treated and untreated homesteads. The outcomes were achieved by low coverage and using only 1-2% of the quantity of insecticide as normally required for IRS, indicating the potential cost-effectiveness of this method. Implications for programmatic deployment of this vector control method are discussed., Competing Interests: The authors have declared that no competing interests exist.

Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all restaurants, pubs and cafes being ordered to close on 20th March, followed by a "stay at home" order on the 23rd March and the closure of all non-essential retail outlets for an indefinite period. Government agencies are presently analysing how best to develop an exit strategy from these measures and to determine how the epidemic may progress once measures are lifted. Mathematical models are currently providing short and long term forecasts regarding the future course of the COVID-19 outbreak in the UK to support evidence-based policymaking. We present a deterministic, age-structured transmission model that uses real-time data on confirmed cases requiring hospital care and mortality to provide up-to-date predictions on epidemic spread in ten regions of the UK. The model captures a range of age-dependent heterogeneities, reduced transmission from asymptomatic infections and produces a good fit to the key epidemic features over time. We simulated a suite of scenarios to assess the impact of differing approaches to relaxing social distancing measures from 7th May 2020 on the estimated number of patients requiring inpatient and critical care treatment, and deaths. With regard to future epidemic outcomes, we investigated the impact of reducing compliance, ongoing shielding of elder age groups, reapplying stringent social distancing measures using region based triggers and the role of asymptomatic transmission. We find that significant relaxation of social distancing measures from 7th May onwards can lead to a rapid resurgence of COVID-19 disease and the health system being quickly overwhelmed by a sizeable, second epidemic wave. In all considered age-shielding based strategies, we projected serious demand on critical care resources during the course of the pandemic. The reintroduction and release of strict measures on a regional basis, based on ICU bed occupancy, results in a long epidemic tail, until the second half of 2021, but ensures that the health service is protected by reintroducing social distancing measures for all individuals in a region when required. Our work confirms the effectiveness of stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. It also provides strong evidence to support the need for a cautious, measured approach to relaxation of lockdown measures, to protect the most vulnerable members of society and support the health service through subduing demand on hospital beds, in particular bed occupancy in intensive care units., Competing Interests: The authors have declared that no competing interests exist.

Humans alter the environment at unprecedented rates through habitat destruction, nutrient pollution and the application of agrochemicals. This has recently been proposed to act as a potentially significant driver of pathogen-carrying mosquito species (disease vectors) that pose a health risk to humans and livestock. Here, we use a unique set of locations along a large geographical gradient to show that landscapes disturbed by a variety of anthropogenic stressors are consistently associated with vector-dominated mosquito communities for a wide range of human and livestock infections. This strongly suggests that human alterations to the environment promote the presence and abundance of disease vectors across large spatial extents. As such, it warrants further studies aimed at unravelling mechanisms underlying vector prevalence in mosquito communities, and opens up new opportunities for preventative action and predictive modelling of vector borne disease risks in relation to degradation of natural ecosystems.

Background: Assessing adult mosquito populations is an important component of disease surveillance programs and ecosystem health assessments. Inference from adult trapping datasets involves comparing populations across space and time, but comparisons based on different trapping methods may be biased if traps have different efficiencies or sample different subsets of the mosquito community., Methods: We compared four widely-used trapping methods for adult mosquito data collection in Kruger National Park (KNP), South Africa: Centers for Disease Control miniature light trap (CDC), Biogents Sentinel trap (BG), Biogents gravid Aedes trap (GAT) and a net trap. We quantified how trap choice and sampling effort influence inferences on the regional distribution of mosquito abundance, richness and community composition., Results: The CDC and net traps together collected 96% (47% and 49% individually) of the 955 female mosquitoes sampled and 100% (85% and 78% individually) of the 40 species or species complexes identified. The CDC and net trap also identified similar regional patterns of community composition. However, inference on the regional patterns of abundance differed between these traps because mosquito abundance in the net trap was influenced by variation in weather conditions. The BG and GAT traps collected significantly fewer mosquitoes, limiting regional comparisons of abundance and community composition., Conclusions: This study represents the first systematic assessment of trapping methods in natural savanna ecosystems in southern Africa. We recommend the CDC trap or the net trap for future monitoring and surveillance programs.

Novel parasites can have wide-ranging impacts, not only on host populations, but also on the resident parasite community. Historically, impacts of novel parasites have been assessed by examining pairwise interactions between parasite species. However, parasite communities are complex networks of interacting species. Here we used multivariate taxonomic and trait-based approaches to determine how parasite community composition changed when African buffalo ( Syncerus caffer ) acquired an emerging disease, bovine tuberculosis (BTB). Both taxonomic and functional parasite richness increased significantly in animals that acquired BTB than in those that did not. Thus, the presence of BTB seems to catalyze extraordinary shifts in community composition. There were no differences in overall parasite taxonomic composition between infected and uninfected individuals, however. The trait-based analysis revealed an increase in direct-transmitted, quickly replicating parasites following BTB infection. This study demonstrates that trait-based approaches provide insight into parasite community dynamics in the context of emerging infections., Competing Interests: The authors declare no conflict of interest.

Background: Mosquito population dynamics are driven by large-scale (e.g. climatological) and small-scale (e.g. ecological) factors. While these factors are known to independently influence mosquito populations, it remains uncertain how drivers that simultaneously operate under natural conditions interact to influence mosquito populations. We, therefore, developed a well-controlled outdoor experiment to assess the interactive effects of two ecological drivers, predation and nutrient availability, on mosquito life history traits under multiple temperature regimes., Methods: We conducted a temperature-controlled mesocosm experiment in Kruger National Park, South Africa, with the yellow fever mosquito, Aedes aegypti. We investigated how larval survival, emergence and development rates were impacted by the presence of a locally-common invertebrate predator (backswimmers Anisops varia Fieber (Notonectidae: Hemiptera), nutrient availability (oligotrophic vs eutrophic, reflecting field conditions), water temperature, and interactions between each driver., Results: We observed that the effects of predation and temperature both depended on eutrophication. Predation caused lower adult emergence in oligotrophic conditions but higher emergence under eutrophic conditions. Higher temperatures caused faster larval development rates in eutrophic but not oligotrophic conditions., Conclusions: Our study shows that ecological bottom-up and top-down drivers strongly and interactively govern mosquito life history traits for Ae. aegypti populations. Specifically, we show that eutrophication can inversely affect predator-prey interactions and mediate the effect of temperature on mosquito survival and development rates. Hence, our results suggest that nutrient pollution can overrule biological constraints on natural mosquito populations and highlights the importance of studying multiple factors.

Domestic swine production in the United States is a critical economic and food security industry, yet there is currently no large-scale quantitative assessment of swine shipments available to support risk assessments. In this study, we provide a national-level characterization of the swine industry by quantifying the demographic (i.e. age, sex) patterns, spatio-temporal patterns, and the production diversity within swine shipments. We characterize annual networks of swine shipments using a 30% stratified sample of Interstate Certificates of Veterinary Inspection (ICVI), which are required for the interstate movement of agricultural animals. We used ICVIs in 2010 and 2011 from eight states that represent 36% of swine operations and 63% of the U.S. swine industry. Our analyses reflect an integrated and spatially structured industry with high levels of spatial heterogeneity. Most shipments carried young swine for feeding or breeding purposes and carried a median of 330 head (range: 1-6,500). Geographically, most shipments went to and were shipped from Iowa, Minnesota, and Nebraska. This work, therefore, suggests that although the swine industry is variable in terms of its size and type of swine, counties in states historically known for breeding and feeding operations are consistently more central to the shipment network.

Mathematical models are key tools for the development of surveillance, preparedness and response plans for the potential events of emerging and introduced foreign animal diseases. Creating these types of plans requires data; when data are incomplete, mathematical models can help fill in missing information, provided they are informed by the data that are available. In the United States, the most complete national-scale data available on cattle shipments are based on Interstate Certificates of Veterinary Inspection, which track the shipment of cattle between states; data on intrastate cattle shipments are lacking. Here we develop four new datasets on intrastate cattle shipments in the U.S., including an expert elicitation survey covering 19 states and territories and three state-level brand inspection data sets. The expert elicitation survey provides estimates on the proportion of shipments that travel interstate over multiple regions of the U.S. These survey data also identify differences in shipment patterns between regions, cattle commodity types, and sectors of the cattle industry. These survey data cover more states than any other source of intrastate data; however, one limitation of these data is the small number of participating experts in many of the states, only seven of the 19 responding states and territories had a group size of three or larger. The brand data sets include origin and destination information for both intra- and interstate shipments. These data, therefore, also provide detailed information on the proportion of interstate shipments in three Western states, including the temporal and geographic variation in shipments. Because the survey and brand data overlap in the Western U.S., they can be compared. We find that in the Western U.S. the expert estimates of the overall proportion of cattle shipments matched the brand data well. However, the experts estimated that there would be larger differences in beef and dairy shipments than the brand data show. This suggests the cattle industries in the West may be sending similar proportions of commodity specific cattle shipments over state lines. We additionally used the expert survey data to explore how differences in the proportion of interstate shipments can change predictions about cattle shipment patterns using the example of model-guided suggestions for targeted surveillance in Texas. Together these four data sets are the most extensive and geographically comprehensive information to date on intrastate cattle shipments. Additionally, our analyses on predicted shipment patterns suggest that assumptions about intrastate shipments could have consequences for targeted surveillance., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Disease acts as a powerful driver of evolution in natural host populations, yet individuals in a population often vary in their susceptibility to infection. Energetic trade-offs between immune and reproductive investment lead to the evolution of distinct life history strategies, driven by the relative fitness costs and benefits of resisting infection. However, examples quantifying the cost of resistance outside of the laboratory are rare. Here, we observe two distinct forms of resistance to bovine tuberculosis (bTB), an important zoonotic pathogen, in a free-ranging African buffalo ( Syncerus caffer ) population. We characterize these phenotypes as "infection resistance," in which hosts delay or prevent infection, and "proliferation resistance," in which the host limits the spread of lesions caused by the pathogen after infection has occurred. We found weak evidence that infection resistance to bTB may be heritable in this buffalo population ( h 2  = 0.10) and comes at the cost of reduced body condition and marginally reduced survival once infected, but also associates with an overall higher reproductive rate. Infection-resistant animals thus appear to follow a "fast" pace-of-life syndrome, in that they reproduce more quickly but die upon infection. In contrast, proliferation resistance had no apparent costs and was associated with measures of positive host health-such as having a higher body condition and reproductive rate. This study quantifies striking phenotypic variation in pathogen resistance and provides evidence for a link between life history variation and a disease resistance trait in a wild mammalian host population.

Coinfecting parasites and pathogens remain a leading challenge for global public health due to their consequences for individual-level infection risk and disease progression. However, a clear understanding of the population-level consequences of coinfection is lacking. Here, we constructed a model that includes three individual-level effects of coinfection: mortality, fecundity, and transmission. We used the model to investigate how these individual-level consequences of coinfection scale up to produce population-level infection patterns. To parameterize this model, we conducted a 4-y cohort study in African buffalo to estimate the individual-level effects of coinfection with two bacterial pathogens, bovine tuberculosis (bTB) and brucellosis, across a range of demographic and environmental contexts. At the individual level, our empirical results identified bTB as a risk factor for acquiring brucellosis, but we found no association between brucellosis and the risk of acquiring bTB. Both infections were associated with reductions in survival and neither infection was associated with reductions in fecundity. The model reproduced coinfection patterns in the data and predicted opposite impacts of coinfection at individual and population scales: Whereas bTB facilitated brucellosis infection at the individual level, our model predicted the presence of brucellosis to have a strong negative impact on bTB at the population level. In modeled populations where brucellosis was present, the endemic prevalence and basic reproduction number ([Formula: see text]) of bTB were lower than in populations without brucellosis. Therefore, these results provide a data-driven example of competition between coinfecting pathogens that occurs when one pathogen facilitates secondary infections at the individual level., Competing Interests: The authors declare no conflict of interest.

Adequate predictions of mosquito-borne disease risk require an understanding of the relevant drivers governing mosquito populations. Since previous studies have focused mainly on the role of temperature, here we assessed the effects of other important ecological variables (predation, nutrient availability, presence of conspecifics) in conjunction with the role of temperature on mosquito life history parameters. We carried out two mesocosm experiments with the common brown house mosquito, Culex pipiens, a confirmed vector for West Nile Virus, Usutu and Sindbis, and a controphic species; the harlequin fly, Chironomus riparius. The first experiment quantified interactions between predation by Notonecta glauca L. (Hemiptera: Notonectidae) and temperature on adult emergence. The second experiment quantified interactions between nutrient additions and temperature on larval mortality and adult emergence. Results indicate that 1) irrespective of temperature, predator presence decreased mosquito larval survival and adult emergence by 20-50%, 2) nutrient additions led to a 3-4-fold increase in mosquito adult emergence and a 2-day decrease in development time across all temperature treatments, 3) neither predation, nutrient additions nor temperature had strong effects on the emergence and development rate of controphic Ch. riparius. Our study suggests that, in addition to of effects of temperature, ecological bottom-up (eutrophication) and top-down (predation) drivers can have strong effects on mosquito life history parameters. Current approaches to predicting mosquito-borne disease risk rely on large-scale proxies of mosquito population dynamics, such as temperature, vegetation characteristics and precipitation. Local scale management actions, however, will require understanding of the relevant top-down and bottom-up drivers of mosquito populations.

Risk-based sampling is an essential component of livestock health surveillance because it targets resources towards sub-populations with a higher risk of infection. Risk-based surveillance in U.S. livestock is limited because the locations of high-risk herds are often unknown and data to identify high-risk herds based on shipments are often unavailable. In this study, we use a novel, data-driven network model for the shipments of cattle in the U.S. (the U.S. Animal Movement Model, USAMM) to provide surveillance suggestions for cattle imported into the U.S. from Mexico. We describe the volume and locations where cattle are imported and analyze their predicted shipment patterns to identify counties that are most likely to receive shipments of imported cattle. Our results suggest that most imported cattle are sent to relatively few counties. Surveillance at 10 counties is predicted to sample 22-34% of imported cattle while surveillance at 50 counties is predicted to sample 43%-61% of imported cattle. These findings are based on the assumption that USAMM accurately describes the shipments of imported cattle because their shipments are not tracked separately from the remainder of the U.S. herd. However, we analyze two additional datasets - Interstate Certificates of Veterinary Inspection and brand inspection data - to ensure that the characteristics of potential post-import shipments do not change on an annual scale and are not dependent on the dataset informing our analyses. Overall, these results highlight the utility of USAMM to inform targeted surveillance strategies when complete shipment information is unavailable., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The application of network analysis to cattle shipments broadens our understanding of shipment patterns beyond pairwise interactions to the network as a whole. Such a quantitative description of cattle shipments in the U.S. can identify trade communities, describe temporal shipment patterns, and inform the design of disease surveillance and control strategies. Here, we analyze a longitudinal dataset of beef and dairy cattle shipments from 2009 to 2011 in the United States to characterize communities within the broader cattle shipment network, which are groups of counties that ship mostly to each other. Because shipments occur over time, we aggregate the data at various temporal scales to examine the consistency of network and community structure over time. Our results identified nine large (>50 counties) communities based on shipments of beef cattle in 2009 aggregated into an annual network and nine large communities based on shipments of dairy cattle. The size and connectance of the shipment network was highly dynamic; monthly networks were smaller than yearly networks and revealed seasonal shipment patterns consistent across years. Comparison of the shipment network over time showed largely consistent shipping patterns, such that communities identified on annual networks of beef and diary shipments from 2009 still represented 41-95% of shipments in monthly networks from 2009 and 41-66% of shipments from networks in 2010 and 2011. The temporal aspects of cattle shipments suggest that future applications of the U.S. cattle shipment network should consider seasonal shipment patterns. However, the consistent within-community shipping patterns indicate that yearly communities could provide a reasonable way to group regions for management., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Chronic infections may have negative impacts on wildlife populations, yet their effects are difficult to detect in the absence of long-term population monitoring. Brucella abortus, the bacteria responsible for bovine brucellosis, causes chronic infections and abortions in wild and domestic ungulates, but its impact on population dynamics is not well understood. We report infection patterns and fitness correlates of bovine brucellosis in African buffalo based on (1) 7 years of cross-sectional disease surveys and (2) a 4-year longitudinal study in Kruger National Park (KNP), South Africa. We then used a matrix population model to translate these observed patterns into predicted population-level effects. Annual brucellosis seroprevalence ranged from 8·7% (95% CI = 1·8-15·6) to 47·6% (95% CI = 35·1-60·1) increased with age until adulthood (>6) and varied by location within KNP. Animals were on average in worse condition after testing positive for brucellosis (F = -5·074, P < 0·0001), and infection was associated with a 2·0 (95% CI = 1·1-3·7) fold increase in mortality (χ(2)  = 2·039, P = 0·036). Buffalo in low body condition were associated with lower reproductive success (F = 2·683, P = 0·034), but there was no association between brucellosis and pregnancy or being observed with a calf. For the range of body condition scores observed in the population, the model-predicted growth rate was λ = 1·11 (95% CI = 1·02-1·21) in herds without brucellosis and λ = 1·00 (95% CI = 0·85-1·16) when brucellosis seroprevalence was 30%. Our results suggest that brucellosis infection can potentially result in reduced population growth rates, but because these effects varied with demographic and environmental conditions, they may remain unseen without intensive, longitudinal monitoring., (© 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.)

The ubiquity and importance of parasite co-infections in populations of free-living animals is beginning to be recognized, but few studies have demonstrated differential fitness effects of single infection versus co-infection in free-living populations. We investigated interactions between the emerging bacterial disease bovine tuberculosis (BTB) and the previously existing viral disease Rift Valley fever (RVF) in a competent reservoir host, African buffalo, combining data from a natural outbreak of RVF in captive buffalo at a buffalo breeding facility in 2008 with data collected from a neighbouring free-living herd of African buffalo in Kruger National Park. RVF infection was twice as likely in individual BTB+ buffalo as in BTB- buffalo, which, according to a mathematical model, may increase RVF outbreak size at the population level. In addition, co-infection was associated with a far higher rate of fetal abortion than other infection states. Immune interactions between BTB and RVF may underlie both of these interactions, since animals with BTB had decreased innate immunity and increased pro-inflammatory immune responses. This study is one of the first to demonstrate how the consequences of emerging infections extend beyond direct effects on host health, potentially altering the dynamics and fitness effects of infectious diseases that had previously existed in the ecosystem on free-ranging wildlife populations., (© 2015 The Author(s) Published by the Royal Society. All rights reserved.)

Brucellosis is a disease of veterinary and public health importance worldwide. In sub-Saharan Africa, where the bacterium Brucella abortus has been identified in several free-ranging wildlife species, successful disease control may be dependent on accurate detection in wildlife reservoirs, including African buffalo (Syncerus caffer). We estimated the sensitivity and specificity of a commercial enzyme-linked immunosorbent assay (ELISA) (IDEXX Brucellosis Serum Ab test, IDEXX Laboratories, Westbrook, Maine, USA) for B. abortus based on a data set of 571 serum samples from 258 buffalo in the Kruger National Park, South Africa. We defined a pseudogold standard test result as those buffalo that were consistently positive or negative on two additional serologic tests, namely, the rose bengal test (RBT) and the complement fixation test (CFT). The ELISA's cutoff value was selected using receiver operating characteristics analysis, the pseudogold standard, and a threshold criterion that maximizes the total sensitivity and specificity. Then, we estimated the sensitivity and specificity of all three tests using Bayesian inference and latent class analysis. The ELISA had an estimated sensitivity of 0.928 (95% Bayesian posterior credibility interval [95% BCI] = 0.869-0.974) and specificity of 0.870 (95% BCI = 0.836-0.900). Compared with the ELISA, the RBT had a higher estimated sensitivity of 0.986 (95% BCI = 0.928-0.999), and both the RBT and CFT had higher specificities, estimated to be 0.992 (95% BCI = 0.971-0.996) and 0.998 (95% BCI = 0.992-0.999), respectively. Therefore, no single serologic test perfectly detected the antibody. However, after adjustment of cutoff values for South African conditions, the IDEXX Brucellosis Serum Ab Test may be a valuable additional screening test for brucellosis in Kruger National Park's African buffalo.

Co-infections are common in natural populations and interactions among co-infecting parasites can significantly alter the transmission and host fitness costs of infection. Because both exposure and susceptibility vary over time, predicting the consequences of parasite interactions on host fitness and disease dynamics may require detailed information on their effects across different environmental (season) and host demographic (age, sex) conditions. This study examines five years of seasonal health and co-infection patterns in African buffalo (Syncerus caffer). We use data on two groups of gastrointestinal parasites, coccidia and nematodes, to test the hypothesis that co-infection and season interact to influence (1) parasite prevalence and intensity and (2) three proxies for host fitness: host pregnancy, host body condition, and parasite aggregation. Our results suggest that season-dependent interactions between nematodes and coccidia affect the distribution of infections. Coccidia prevalence, coccidia intensity and nematode prevalence were sensitive to factors that influence host immunity and exposure (age, sex, and season) but nematode intensity was most strongly predicted by co-infection with coccidia and its interaction with season. The influence of co-infection on host body condition and parasite aggregation occurred in season-dependent manner. Co-infected buffalo in the early wet season were in worse condition, had a less aggregated distribution of nematode parasites, and lower nematode infection intensity than buffalo infected with nematodes alone. We did not detect an effect of infection or co-infection on host pregnancy. These results suggest that demographic and seasonal variation may mediate the effects of parasites, and their interactions, on the distribution and fitness costs of infection.