African swine fever in wild boar: investigating model assumptions and structure

African swine fever (ASF) is a highly virulent viral disease that affects both domestic pigs and wild boar. Current ASF transmission in Europe is in part driven by wild boar populations, which act as a disease reservoir. Wild boar are abundant throughout Europe and are highly social animals with complex social organisation. Despite the known importance of wild boar in ASF spread and persistence, there remain knowledge gaps surrounding wild boar transmission. To investigate the influence of density-contact functions and wild boar social structure on disease dynamics, we developed a wild boar modelling framework. The framework included an ordinary differential equation model, a homogeneous stochastic model, and various network-based stochastic models that explicitly included wild boar social grouping. We found that power law functions (transmission $\propto$ density$^{0.5}$) and frequency-based density-contact functions were best able to reproduce recent Baltic outbreaks; however, power law function models predicted considerable carcass transmission, while frequency-based models had negligible carcass transmission. Furthermore, increased model heterogeneity caused a decrease in the relative importance of carcass-based transmission. The different dominant transmission pathways predicted by each model type affected the efficacy of potential interventions, which highlights the importance of evaluating model type and structure when modelling systems with uncertainties.Comment: 37 pages. 11 figures in main, 9 figures in appendix. 3 tables in main, 8 tables in appendi

Modelling diverse sources of Clostridium difficile in the community: importance of animals, infants and asymptomatic carriers

Clostridium difficile infections (CDIs) affect patients in hospitals and in the community, but the relative importance of transmission in each setting is unknown. We developed a mathematical model of C. difficile transmission in a hospital and surrounding community that included infants, adults, and transmission from animal reservoirs. We assessed the role of these transmission routes in maintaining disease and evaluated the recommended classification system for hospital and community-acquired CDIs.This work was supported by an Australian National Health and Medical Council Senior Research Fellowship [#1058878 to A.C.A.C.] and an Australian Government Research Training Program Scholarship to A.M

Some simple rules for estimating reproduction numbers in the presence of reservoir exposure or imported cases

For many diseases, the basic reproduction number () is a threshold parameter for disease extinction or survival in isolated populations. However no human population is fully isolated from other human or animal populations. We use compartmental models to derive simple rules for the basic reproduction number in populations where an endemic disease is sustained by a combination of local transmission within the population and exposure from some other source: either a reservoir exposure or imported cases. We introduce the idea of a reservoir-driven or importation-driven disease: diseases that would become extinct in the population of interest without reservoir exposure or imported cases (since ), but nevertheless may be sufficiently transmissible that many or most infections are acquired from humans in that population. We show that in the simplest case, if and only if the proportion of infections acquired from the external source exceeds the disease prevalence and explore how population heterogeneity and the interactions of multiple strains affect this rule. We apply these rules in two case studies of Clostridium difficile infection and colonisation: C. difficile in the hospital setting accounting for imported cases, and C. difficile in the general human population accounting for exposure to animal reservoirs. We demonstrate that even the hospital-adapted, highly-transmissible NAP1/RT027 strain of C. difficile had a reproduction number <1 in a landmark study of hospitalised patients and therefore was sustained by colonised and infected admissions to the study hospital. We argue that C. difficile should be considered reservoir-driven if as little as 13.0% of transmission can be attributed to animal reservoirsAustralian Government Research Training Program Scholarshi

Clostridium difficile classification overestimates hospital acquired infections

BACKGROUND Clostridium difficile infections are common among hospitalised patients, with some infections acquired in hospital and others in the community. International guidelines classify cases as hospital-acquired if symptom onset occurs >2 days after admission. This classification informs surveillance and infection control, but has not been verified by empirical or modelling studies. AIMS To assess current classification of C. difficile acquisition using a simulation model as a gold standard. METHODS We simulated C. difficile transmission in a range of hospital scenarios. We calculated the sensitivity, specificity and precision of classifications that use cut-offs ranging from 0.25 hours to 40 days. We identified the optimal cut-off that correctly estimated the proportion of cases that were hospital acquired and the balanced cut-off that had equal sensitivity and specificity. FINDINGS The recommended two-day cut-off overestimated the incidence of hospital-acquired cases in all scenarios and by >100% in the base scenario. The two-day cut-off had good sensitivity (96%) but poor specificity (48%) and precision (52%) to identify cases acquired during the current hospitalisation. A five-day cut-off was balanced and a six-day cut-off was optimal in the base scenario. The optimal and balanced cut-offs were more than two days for nearly all scenarios considered (ranges four to nine days and two to eight days). CONCLUSIONS Current guidelines for classifying C. difficile infections overestimate the proportion of cases acquired in hospital in all model scenarios. To reduce misclassification bias, an infection should be classified as being acquired prior to admission if symptoms begin within five days of admission

Modelling diverse sources of Clostridium difficile in the community: importance of animals, infants and asymptomatic carriers

Clostridium difficile infections (CDIs) affect patients in hospitals and in the community, but the relative importance of transmission in each setting is unknown. We developed a mathematical model of C. difficile transmission in a hospital and surrounding community that included infants, adults, and transmission from animal reservoirs. We assessed the role of these transmission routes in maintaining disease and evaluated the recommended classification system for hospital and community-acquired CDIs. The reproduction number in the hospital was <1 (range: 0.16-0.46) for all scenarios. Outside the hospital, the reproduction number was >1 for nearly all scenarios without transmission from animal reservoirs (range: 1.0-1.34). However, the reproduction number for the human population was 3.5-26.0%) of human exposures originated from animal reservoirs. Symptomatic adults accounted for <10% transmission in the community. Under conservative assumptions, infants accounted for 17% of community transmission. An estimated 33-40% of community-acquired cases were reported but 28-39% of these reported cases were misclassified as hospital-acquired by recommended definitions. Transmission could be plausibly sustained by asymptomatically colonized adults and infants in the community or exposure to animal reservoirs, but not hospital transmission alone. Underreporting of community-onset cases and systematic misclassification underplays the role of community transmission

Modelling lymphatic filariasis elimination in American Samoa: GEOFIL predicts need for new targets and six rounds of mass drug administration

Background: As part of the global effort to eliminate the debilitating mosquito-borne disease lymphatic filariasis (LF), seven rounds of two-drug (diethylcarbamazine and albendazole) mass drug administration (MDA) were conducted in American Samoa over 2000–2006. However subsequent surveys demonstrated ongoing transmission prompting further rounds of three-drug (diethylcarbamazine, albendazole, and ivermectin) MDA starting in 2018. Methods: We extend GEOFIL, a spatially-explicit agent-based model of LF transmission to predict the probability and timing of the local elimination or resurgence of LF for different MDA scenarios starting in 2018: two-drug vs. three-drug MDA, two to seven annual rounds, and population coverage rates of 55–75%. We developed an interactive visualisation comparing the effect of MDA strategies on different outcomes. Results: At least six annual rounds of three-drug MDA treating 75% of the population were required to achieve LF elimination in American Samoa by 2035 in > 50% of simulations. In scenarios where MDA did not achieve elimination, prevalence doubled approximately every three years, even if MDA reduced antigen prevalence to <1% (the target recommended by the World Health Organisation). Prevalence in six- and seven-year-old children was approximately one quarter of the prevalence in the general population. Conclusion: The three rounds of three-drug MDA conducted in 2018, 2019, and 2021 may have come close to WHO targets but are unlikely to interrupt LF transmission in American Samoa without further interventions. The recommended post-MDA surveillance strategy of testing primarily six and seven-year-old children will delay detection of resurgence compared to population representative surveys. The recommended elimination targets (reducing antigen prevalence below 0.5%, 1%, or 2%) may not be sufficient to interrupt transmission in countries with LF epidemiology like American Samoa. Alternative surveillance strategies and interventions designed to identify and eliminate spatially localized residual transmission may need to be considered. Interactive visualisations may assist decision-makers to choose locally appropriate strategies

Evaluating Molecular Xenomonitoring as a Tool for Lymphatic Filariasis Surveillance in Samoa, 2018–2019

Molecular xenomonitoring (MX), the detection of filarial DNA in mosquitoes using molecular methods (PCR), is a potentially useful surveillance strategy for lymphatic filariasis (LF) elimination programs. Delay in filarial antigen (Ag) clearance post-treatment is a limitation of using human surveys to provide an early indicator of the impact of mass drug administration (MDA), and MX may be more useful in this setting. We compared prevalence of infected mosquitoes pre- and post-MDA (2018 and 2019) in 35 primary sampling units (PSUs) in Samoa, and investigated associations between the presence of PCR-positive mosquitoes and Ag-positive humans. We observed a statistically significant decline in estimated mosquito infection prevalence post-MDA at the national level (from 0.9% to 0.3%, OR 0.4) but no change in human Ag prevalence during this time. Ag prevalence in 2019 was higher in randomly selected PSUs where PCR-positive pools were detected (1.4% in ages 5–9; 4.8% in ages ≥10), compared to those where PCR-positive pools were not detected (0.2% in ages 5–9; 3.2% in ages ≥10). Our study provides promising evidence for MX as a complement to human surveys in post-MDA surveillance

Mathematical models of Clostridium diffcile transmission

Clostridium difficile infections (CDIs) are some of the most common hospital-acquired infections and the most common cause of antibiotic-associated diarrhoea. CDIs lead to great loss of life, severe health outcomes, and incur very high financial costs through treatment, extended hospital stays, and readmissions. Despite extensive research and many resources committed to the prevention and treatment CDIs in hospitalised patients, hospitals continue to be hotspots for this disease. Meanwhile, there is an emerging awareness of the burden this disease places on the broader community including patients who have not recently been hospitalised. In the community approximately 5% of adults and a higher proportion of infants are asymptomatically colonised. Colonisation is also common in livestock and the pathogen has been isolated from meat and vegetables. However, the various sources of transmission in the community and the consequences for infections within and beyond hospitals are not well understood. This thesis develops and employs mathematical models of C. difficile transmission to explore three themes: improving models to capture the complex epidemiology of C. difficile, populations that sustain C. difficile transmission, and the classifi cation of CDIs as hospital or community-acquired. Addressing the fi rst theme, I argue that the essential epidemiology of C. difficile is captured by modelling the interactions of three key factors: pathogen, immunity, and gut flora. I argue that modelling transmission in an integrated model of adults and infants across hospitals and communities provides insights that hospital-only and adult-only models cannot. By incorporating seasonality into these models, I argue that seasonal variation of antibiotic prescription rates is more likely to be the main driver of CDI seasonality than seasonal transmission. In the second theme, I argue that most hospitals -- though hotspots for transmission -- are not disease sustaining populations. Instead, transmission outside hospitals maintains the disease in the hospital and community. I argue that reducing transmission in the hospital cannot eliminate the disease in the broader population, but that reducing transmission from adults or infants in the community could interrupt transmission in the human population. Similarly, I argue that C. difficile in the community may be driven by transmission from animal reservoirs if as few as 3.5-26.0% of human infections are acquired from animal or food sources. In the final theme, I argue that an illusion of hospital-driven disease is in part perpetuated by surveillance defi nitions that systematically misclassify many community-acquired cases as hospital-acquired. The incubation period for C. difficile infections often exceeds the two-day or three-day cut-offs commonly used to classify patients recently admitted to hospital. I argue that many patients who acquire the pathogen prior to admission develop symptoms after the cut-off and are therefore incorrectly classifi ed as having acquired the infection during their hospital stay. Furthermore, I argue that time since hospital discharge is a poor indicator of whether a CDI is hospital or community-acquired