Modelling respiratory syncytial virus age-specific risk of hospitalisation in term and preterm infants.

BACKGROUND: Respiratory syncytial virus (RSV) is the most common cause of acute lower respiratory infections in children worldwide. The highest incidence of severe disease is in the first 6 months of life, with infants born preterm at greatest risk for severe RSV infections. The licensure of new RSV therapeutics (a long-acting monoclonal antibody and a maternal vaccine) in Europe, USA, UK and most recently in Australia, has driven the need for strategic decision making on the implementation of RSV immunisation programs. Data driven approaches, considering the local RSV epidemiology, are critical to advise on the optimal use of these therapeutics for effective RSV control. METHODS: We developed a dynamic compartmental model of RSV transmission fitted to individually-linked population-based laboratory, perinatal and hospitalisation data for 2000-2012 from metropolitan Western Australia (WA), stratified by age and prior exposure. We account for the differential risk of RSV-hospitalisation in full-term and preterm infants (defined as < 37 weeks gestation). We formulated a function relating age, RSV exposure history, and preterm status to the risk of RSV-hospitalisation given infection. RESULTS: The age-to-risk function shows that risk of hospitalisation, given RSV infection, declines quickly in the first 12 months of life for all infants and is 2.6 times higher in preterm compared with term infants. The hospitalisation risk, given infection, declines to < 10% of the risk at birth by age 7 months for term infants and by 9 months for preterm infants. CONCLUSIONS: The dynamic model, using the age-to-risk function, characterises RSV epidemiology for metropolitan WA and can now be extended to predict the impact of prevention measures. The stratification of the model by preterm status will enable the comparative assessment of potential strategies in the extended model that target this RSV risk group relative to all-population approaches. Furthermore, the age-to-risk function developed in this work has wider relevance to the epidemiological characterisation of RSV.

COVID-19 vaccination strategies in settings with limited rollout capacity: a mathematical modelling case study in Sierra Leone.

BACKGROUND: COVID-19 vaccine coverage in low- and middle-income countries continues to be challenging. As supplies increase, coverage is increasingly becoming determined by rollout capacity. METHODS: We developed a deterministic compartmental model of COVID-19 transmission to explore how age-, risk-, and dose-specific vaccine prioritisation strategies can minimise severe outcomes of COVID-19 in Sierra Leone. RESULTS: Prioritising booster doses to older adults and adults with comorbidities could reduce the incidence of severe disease by 23% and deaths by 34% compared to the use of these doses as primary doses for all adults. Providing a booster dose to pregnant women who present to antenatal care could prevent 38% of neonatal deaths associated with COVID-19 infection during pregnancy. The vaccination of children is not justified unless there is sufficient supply to not affect doses delivered to adults. CONCLUSIONS: Our paper supports current WHO SAGE vaccine prioritisation guidelines (released January 2022). Individuals who are at the highest risk of developing severe outcomes should be prioritised, and opportunistic vaccination strategies considered in settings with limited rollout capacity.

Source attribution of campylobacteriosis in Australia, 2017-2019.

Campylobacter jejuni and Campylobacter coli infections are the leading cause of foodborne gastroenteritis in high-income countries. Campylobacter colonizes a variety of warm-blooded hosts that are reservoirs for human campylobacteriosis. The proportions of Australian cases attributable to different animal reservoirs are unknown but can be estimated by comparing the frequency of different sequence types in cases and reservoirs. Campylobacter isolates were obtained from notified human cases and raw meat and offal from the major livestock in Australia between 2017 and 2019. Isolates were typed using multi-locus sequence genotyping. We used Bayesian source attribution models including the asymmetric island model, the modified Hald model, and their generalizations. Some models included an "unsampled" source to estimate the proportion of cases attributable to wild, feral, or domestic animal reservoirs not sampled in our study. Model fits were compared using the Watanabe-Akaike information criterion. We included 612 food and 710 human case isolates. The best fitting models attributed >80% of Campylobacter cases to chickens, with a greater proportion of C. coli (>84%) than C. jejuni (>77%). The best fitting model that included an unsampled source attributed 14% (95% credible interval [CrI]: 0.3%-32%) to the unsampled source and only 2% to ruminants (95% CrI: 0.3%-12%) and 2% to pigs (95% CrI: 0.2%-11%) The best fitting model that did not include an unsampled source attributed 12% to ruminants (95% CrI: 1.3%-33%) and 6% to pigs (95% CrI: 1.1%-19%). Chickens were the leading source of human Campylobacter infections in Australia in 2017-2019 and should remain the focus of interventions to reduce burden.

The Cost of Foodborne Illness and Its Sequelae in Australia Circa 2019.

Foodborne illnesses cause a significant health burden, with Campylobacter and norovirus the most common causes of illness and Salmonella a common cause of hospitalization and occasional cause of death. Estimating the cost of illness can assist in quantifying this health burden, with pathogen-specific costs informing prioritization of interventions. We used a simulation-based approach to cost foodborne disease in Australia, capturing the cost of premature mortality, direct costs of nonfatal illness (including health care costs, medications, and tests), indirect costs of illness due to lost productivity, and costs associated with pain and suffering. In Australia circa 2019, the cost in Australian Dollars (AUD) of foodborne illness and its sequelae was 2.44 billion (90% uncertainty interval 1.65-3.68) each year, with the highest pathogen-specific costs for Campylobacter, non-typhoidal Salmonella, non-Shiga toxin-producing pathogenic Escherichia coli, and norovirus. The highest cost per case was for Listeria monocytogenes (AUD 776,000). Lost productivity was the largest component cost for foodborne illness due to all causes and for most individual pathogens; the exceptions were pathogens causing more severe illness such as Salmonella and L. monocytogenes, where premature mortality was the largest component cost. Foodborne illness results in a substantial cost to Australia; interventions to improve food safety across industry, retail, and consumers are needed to maintain public health safety.

Opening up safely: public health system requirements for ongoing COVID-19 management based on evaluation of Australia's surveillance system performance.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) community transmission was eliminated in Australia from 1/11/2020 to 30/6/2021, allowing evaluation of surveillance system performance in detecting novel outbreaks, including against variants of concern (VoCs). This paper aims to define system requirements for coronavirus disease 2019 (COVID-19) surveillance under future transmission and response scenarios, based on surveillance system performance to date. METHODS: This study described and evaluated surveillance systems and epidemiological characteristics of novel outbreaks based on publicly available data, and assessed surveillance system sensitivity and timeliness in outbreak detection. These findings were integrated with analysis of other critical COVID-19 public health measures to establish future COVID-19 management requirements. RESULTS: Twenty-five epidemiologically distinct outbreaks and five distinct clusters were identified in the study period, all linked through genomic sequencing to novel introductions from international travellers. Seventy percent (21/30) were detected through community testing of people with acute respiratory illness, and 30% (9/30) through quarantine screening. On average, 2.07% of the State population was tested in the week preceding detection for those identified through community surveillance. From 17/30 with publicly available data, the average time from seeding to detection was 4.9 days. One outbreak was preceded by unexpected positive wastewater results. Twenty of the 24 outbreaks in 2021 had publicly available sequencing data, all of which identified VoCs. A surveillance strategy for future VoCs similar to that used for detecting SARS-CoV-2 would require a 100-1000-fold increase in genomic sequencing capacity compared to the study period. Other essential requirements are maintaining outbreak response capacity and developing capacity to rapidly engineer, manufacture, and distribute variant vaccines at scale. CONCLUSIONS: Australia's surveillance systems performed well in detecting novel introduction of SARS-CoV-2 while community transmission was eliminated; introductions were infrequent and case numbers were low. Detection relied on quarantine screening and community surveillance in symptomatic members of the general population, supported by comprehensive genomic sequencing. Once vaccine coverage is maximised, future COVID-19 control should shift to detection of SARS-CoV-2 VoCs, requiring maintenance of surveillance systems and testing all international arrivals, alongside greatly increased genomic sequencing capacity. Effective government support of localised public health response mechanisms and engagement of all sectors of the community is crucial to current and future COVID-19 management.

Source attribution of salmonellosis by time and geography in New South Wales, Australia.

BACKGROUND: Salmonella is a major cause of zoonotic illness around the world, arising from direct or indirect contact with a range of animal reservoirs. In the Australian state of New South Wales (NSW), salmonellosis is believed to be primarily foodborne, but the relative contribution of animal reservoirs is unknown. METHODS: The analysis included 4543 serotyped isolates from animal reservoirs and 30,073 serotyped isolates from domestically acquired human cases in NSW between January 2008 and August 2019. We used a Bayesian source attribution methodology to estimate the proportion of foodborne Salmonella infections attributable to broiler chickens, layer chickens, ruminants, pigs, and an unknown or unsampled source. Additional analyses included covariates for four time periods and five levels of rurality. RESULTS: A single serotype, S. Typhimurium, accounted for 65-75% of included cases during 2008-2014 but < 50% during 2017-2019. Attribution to layer chickens was highest during 2008-2010 (48.7%, 95% CrI 24.2-70.3%) but halved by 2017-2019 (23.1%, 95% CrI 5.7-38.9%) and was lower in the rural and remote populations than in the majority urban population. The proportion of cases attributed to the unsampled source was 11.3% (95% CrI 1.2%-22.1%) overall, but higher in rural and remote populations. The proportion of cases attributed to pork increased from approximately 20% in 2009-2016 to approximately 40% in 2017-2019, coinciding with a rise in cases due to Salmonella ser. 4,5,12:i:-. CONCLUSION: Layer chickens were likely the primary reservoir of domestically acquired Salmonella infections in NSW circa 2010, but attribution to the source declined contemporaneously with increased vaccination of layer flocks and tighter food safety regulations for the handling of eggs.

Risk factors for campylobacteriosis in Australia: outcomes of a 2018-2019 case-control study.

BACKGROUND: We aimed to identify risk factors for sporadic campylobacteriosis in Australia, and to compare these for Campylobacter jejuni and Campylobacter coli infections. METHODS: In a multi-jurisdictional case-control study, we recruited culture-confirmed cases of campylobacteriosis reported to state and territory health departments from February 2018 through October 2019. We recruited controls from notified influenza cases in the previous 12 months that were frequency matched to cases by age group, sex, and location. Campylobacter isolates were confirmed to species level by public health laboratories using molecular methods. We conducted backward stepwise multivariable logistic regression to identify significant risk factors. RESULTS: We recruited 571 cases of campylobacteriosis (422 C. jejuni and 84 C. coli) and 586 controls. Important risk factors for campylobacteriosis included eating undercooked chicken (adjusted odds ratio [aOR] 70, 95% CI 13-1296) or cooked chicken (aOR 1.7, 95% CI 1.1-2.8), owning a pet dog aged < 6 months (aOR 6.4, 95% CI 3.4-12), and the regular use of proton-pump inhibitors in the 4 weeks prior to illness (aOR 2.8, 95% CI 1.9-4.3). Risk factors remained similar when analysed specifically for C. jejuni infection. Unique risks for C. coli infection included eating chicken pâté (aOR 6.1, 95% CI 1.5-25) and delicatessen meats (aOR 1.8, 95% CI 1.0-3.3). Eating any chicken carried a high population attributable fraction for campylobacteriosis of 42% (95% CI 13-68), while the attributable fraction for proton-pump inhibitors was 13% (95% CI 8.3-18) and owning a pet dog aged < 6 months was 9.6% (95% CI 6.5-13). The population attributable fractions for these variables were similar when analysed by campylobacter species. Eating delicatessen meats was attributed to 31% (95% CI 0.0-54) of cases for C. coli and eating chicken pâté was attributed to 6.0% (95% CI 0.0-11). CONCLUSIONS: The main risk factor for campylobacteriosis in Australia is consumption of chicken meat. However, contact with young pet dogs may also be an important source of infection. Proton-pump inhibitors are likely to increase vulnerability to infection.

Bias Assessment in Outcomes Research: The Role of Relative Versus Absolute Approaches.

OBJECTIVES: Bias assessment tools vary in content and detail, and the method used for assessment may produce different assessment results in a study if not carefully considered. Therefore, taking an approach to the assessment of studies that produces a similar result regardless of the tool used for assessment (tool independence) is important. METHODS: A preexisting study that used 25 different quality scales was assessed to examine tool dependence of 2 common approaches to bias assessments-absolute value judgments (defined as the qualitative risk of bias judgment based on a threshold across studies) and relative ranks (defined as the relative probability toward bias of a study relative to the best assessed study). Agreement between each of the 25 scales and a composite scale (that includes all unique safeguards across all scales) was computed (using the intraclass correlation coefficient [ICC]; consistency). Tool dependence was considered present when the ICCs were inconsistent across the 25 scales for the same study. RESULTS: We found that using relative ranks for tools with different numbers and types of items produced consistent results, with only small differences in the agreement for the various tools with the composite tool, whereas consistency (measured by the ICC) varied considerably when using absolute judgments. Inconsistency is problematic because it means that the assessment result is linked to the scale and not to the study. CONCLUSIONS: Tool independence is an important attribute of a bias assessment tool. On the basis of this study, the use of relative ranks retains tool independence and therefore produces consistent ranks for the same study across tools.

Coronavirus Disease Model to Inform Transmission-Reducing Measures and Health System Preparedness, Australia.

The ability of health systems to cope with coronavirus disease (COVID-19) cases is of major concern. In preparation, we used clinical pathway models to estimate healthcare requirements for COVID-19 patients in the context of broader public health measures in Australia. An age- and risk-stratified transmission model of COVID-19 demonstrated that an unmitigated epidemic would dramatically exceed the capacity of the health system of Australia over a prolonged period. Case isolation and contact quarantine alone are insufficient to constrain healthcare needs within feasible levels of expansion of health sector capacity. Overlaid social restrictions must be applied over the course of the epidemic to ensure systems do not become overwhelmed and essential health sector functions, including care of COVID-19 patients, can be maintained. Attention to the full pathway of clinical care is needed, along with ongoing strengthening of capacity.

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

For many diseases, the basic reproduction number (R0) 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 R0<1), 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, R0<1 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 reservoirs.

Differential antimicrobial susceptibility profiles between symptomatic and asymptomatic non-typhoidal Salmonella infections in Vietnamese children.

Non-typhoidal Salmonella (NTS) serovars, sequences types and antimicrobial susceptibility profiles have specific associations with animal and human infections in Vietnam. Antimicrobial resistance may have an effect on the manifestation of human NTS infections, with isolates from asymptomatic individuals being more susceptible to antimicrobials than those associated with animals and human diarrhoea.

Describing the Epidemiology of Foodborne Outbreaks in New South Wales from 2000 to 2017.

Foodborne disease causes an estimated 4.1 million cases of illness in Australia each year and is responsible for causing many significant common source outbreaks. We analyzed 18 years of foodborne outbreak data collected in New South Wales (NSW), and classified the likely pathogen type responsible for outbreaks of unknown etiology, to track broad trends over time. A total of 869 outbreaks were reported in NSW from 2000 to 2017. The majority (53%) of outbreaks did not have a pathogen identified and underwent pathogen type categorization based on the epidemiology of the outbreak. The proportion of outbreaks due to toxin producing bacteria decreased over time, whereas the proportion of outbreaks due to other bacterial pathogens increased. The proportion of outbreaks due to viral gastroenteritis pathogens had no overall changing trend over time. Bacterial outbreaks had significantly more identified cases and had more hospitalizations than other pathogen type causes. Other features associated with high case numbers, hospitalizations, and deaths in foodborne outbreaks included being due to food contaminated in primary production, involving consumption of raw products, and having evidence of poor sanitation in the food preparation areas. Eggs were the most commonly determined pathogen food source, occurring in 12% of outbreaks; however, most outbreak investigations (77%) did not have a pathogen food source identified. This analysis demonstrates a changing landscape of foodborne outbreaks over time. Increases in outbreaks due to bacterial and viral pathogens coincide with increases in sporadic notifications of the same pathogens, whereas decreases in toxin caused outbreaks followed the introduction of mandatory food safety training in retail food businesses. Recognizing issues in food production and implementing improvements that reduce the number of pathogens in food will be key to reducing the incidence of foodborne outbreaks.

Source Attribution of Salmonella in Macadamia Nuts to Animal and Environmental Reservoirs in Queensland, Australia.

Salmonella enterica is a common contaminant of macadamia nut kernels in the subtropical state of Queensland (QLD), Australia. We hypothesized that nonhuman sources in the plantation environment contaminate macadamia nuts. We applied a modified Hald source attribution model to attribute Salmonella serovars and phage types detected on macadamia nuts from 1998 to 2017 to specific animal and environmental sources. Potential sources were represented by Salmonella types isolated from avian, companion animal, biosolids-soil-compost, equine, porcine, poultry, reptile, ruminant, and wildlife samples by the QLD Health reference laboratory. Two attribution models were applied: model 1 merged data across 1998-2017, whereas model 2 pooled data into 5-year time intervals. Model 1 attributed 47% (credible interval, CrI: 33.6-60.8) of all Salmonella detections on macadamia nuts to biosolids-soil-compost. Wildlife and companion animals were found to be the second and third most important contamination sources, respectively. Results from model 2 showed that the importance of the different sources varied between the different time periods; for example, Salmonella contamination from biosolids-soil-compost varied from 4.4% (CrI: 0.2-11.7) in 1998-2002 to 19.3% (CrI: 4.6-39.4) in 2003-2007, and the proportion attributed to poultry varied from 4.8% (CrI: 1-11) in 2008-2012 to 24% (CrI: 11.3-40.7) in 2013-2017. Findings suggest that macadamia nuts were contaminated by direct transmission from animals with access to the plantations (e.g., wildlife and companion animals) or from indirect transmission from animal reservoirs through biosolids-soil-compost. The findings from this study can be used to guide environmental and wildlife sampling and analysis to further investigate routes of Salmonella contamination of macadamia nuts and propose control options to reduce potential risk of human salmonellosis.

Whole-Genome Sequencing of Salmonella Mississippi and Typhimurium Definitive Type 160, Australia and New Zealand.

We used phylogenomic and risk factor data on isolates of Salmonella enterica serovars Mississippi and Typhimurium definitive type 160 (DT160) collected from human, animal, and environmental sources to elucidate their epidemiology and disease reservoirs in Australia and New Zealand. Sequence data suggested wild birds as a likely reservoir for DT160; animal and environmental sources varied more for Salmonella Mississippi than for Salmonella Typhimurium. Australia and New Zealand isolates sat in distinct clades for both serovars; the median single-nucleotide polymorphism distance for DT160 was 29 (range 8-66) and for Salmonella Mississippi, 619 (range 565-737). Phylogenomic data identified plausible sources of human infection from wildlife and environmental reservoirs and provided evidence supporting New Zealand-acquired DT160 in a group of travelers returning to Australia. Wider use of real-time whole-genome sequencing in new locations and for other serovars may identify sources and routes of transmission, thereby aiding prevention and control.

Modelling high pathogenic avian influenza outbreaks in the commercial poultry industry.

Highly pathogenic avian influenza (HPAI) outbreaks are devastating to poultry industries and pose a risk to human health. There is concern that demand for free-range poultry products could increase the number of HPAI outbreaks by increasing the potential for low pathogenic avian influenza (LPAI) introduction to commercial flocks. We formulate stochastic mathematical models to understand how poultry-housing (barn, free-range and caged) within the meat and layer sectors interacts with a continuous low-level risk of introduction from wild birds, heterogeneity in virus transmission rates and virus mutation probabilities, to affect the risk of HPAI emergence - at both the shed and industry scales. For H5 and H7 viruses, restricted mixing in caged systems, free-range outdoor access and, particularly, production cycle length significantly influence HPAI risk between sectors of the chicken production industry. Results demonstrate how delay between virus mutation and detection, ensuing from the short production cycle, large shed sizes and industry reporting requirements, could mean that HPAI emerges in meat-production sheds but is undetected with few birds affected. We also find that the Australian HPAI outbreak history appears to be better explained by low LPAI introduction rates and low mutation probabilities, rather than extremely rare introduction and relatively high mutation probabilities.

Health Outcomes from Multidrug-Resistant Salmonella Infections in High-Income Countries: A Systematic Review and Meta-Analysis.

BACKGROUND: Salmonella is a leading cause of foodborne enterocolitis worldwide. Antimicrobial use in food animals is the driving force for antimicrobial resistance among Salmonella particularly in high-income countries. Nontyphoidal Salmonella (NTS) infections that are multidrug resistant (MDR) (nonsusceptible to ≥1 agent in ≥3 antimicrobial categories) may result in more severe health outcomes, although these effects have not been systematically examined. We conducted a systematic review and meta-analysis to examine impacts of MDR NTS on disease outcomes in high-income settings. METHODS: We systematically reviewed the literature from scientific databases, including PubMed, Scopus, and grey literature sources, using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. We included peer-reviewed publications of case-control and cohort studies, outbreak investigations, and published theses, imposing no language restriction. We included publications from January 1, 1990 through September 15, 2016 from high-income countries as classified by the World Bank, and extracted data on duration of illness, hospitalization, morbidity and mortality of MDR, and pan-susceptible NTS infections. RESULTS: After removing duplicates, the initial search revealed 4258 articles. After further screening, 16 eligible studies were identified for the systematic review, but, only 9 of these were included in the meta-analysis. NTS serotypes differed among the reported studies, but serotypes Typhimurium, Enteritidis, Newport, and Heidelberg were the most often reported MDR pathogens. Salmonella infections that were MDR were associated with excess bloodstream infections (odds ratio [OR] 1.73; 95% confidence interval [CI] 1.32-2.27), more frequent hospitalizations (OR 2.51; 95% CI 1.38-4.58), and higher mortality (OR 3.54; 95% CI 1.10-11.40) when compared with pan-susceptible isolates. CONCLUSIONS: Our study suggests that MDR NTS infections have more serious health outcomes compared with pan-susceptible strains. With the emergence of MDR Salmonella strains in high-income countries, it is crucial to reduce the use of antimicrobials in animals and humans, and intervene to prevent foodborne infections.

Incorporating Whole-Genome Sequencing into Public Health Surveillance: Lessons from Prospective Sequencing of Salmonella Typhimurium in Australia.

In Australia, the incidence of Salmonella Typhimurium has increased dramatically over the past decade. Whole-genome sequencing (WGS) is transforming public health microbiology, but poses challenges for surveillance. To compare WGS-based approaches with conventional typing for Salmonella surveillance, we performed concurrent WGS and multilocus variable-number tandem-repeat analysis (MLVA) of Salmonella Typhimurium isolates from the Australian Capital Territory (ACT) for a period of 5 months. We exchanged data via a central shared virtual machine and performed comparative genomic analyses. Epidemiological evidence was integrated with WGS-derived data to identify related isolates and sources of infection, and we compared WGS data for surveillance with findings from MLVA typing. We found that WGS data combined with epidemiological data linked an additional 9% of isolates to at least one other isolate in the study in contrast to MLVA and epidemiological data, and 19% more isolates than epidemiological data alone. Analysis of risk factors showed that in one WGS-defined cluster, human cases had higher odds of purchasing a single egg brand. While WGS was more sensitive and specific than conventional typing methods, we identified barriers to uptake of genomic surveillance around complexity of reporting of WGS results, timeliness, acceptability, and stability. In conclusion, WGS offers higher resolution of Salmonella Typhimurium laboratory surveillance than existing methods and can provide further evidence on sources of infection in case and outbreak investigations for public health action. However, there are several challenges that need to be addressed for effective implementation of genomic surveillance in Australia.

Seven Salmonella Typhimurium Outbreaks in Australia Linked by Trace-Back and Whole Genome Sequencing.

Salmonella Typhimurium is a common cause of foodborne illness in Australia. We report on seven outbreaks of Salmonella Typhimurium multilocus variable-number tandem-repeat analysis (MLVA) 03-26-13-08-523 (European convention 2-24-12-7-0212) in three Australian states and territories investigated between November 2015 and March 2016. We identified a common egg grading facility in five of the outbreaks. While no Salmonella Typhimurium was detected at the grading facility and eggs could not be traced back to a particular farm, whole genome sequencing (WGS) of isolates from cases from all seven outbreaks indicated a common source. WGS was able to provide higher discriminatory power than MLVA and will likely link more Salmonella Typhimurium cases between states and territories in the future. National harmonization of Salmonella surveillance is important for effective implementation of WGS for Salmonella outbreak investigations.

Healthcare-Associated Clostridium difficile Infections are Sustained by Disease from the Community.

Clostridium difficile infections (CDIs) are some of the most common hospital-associated infections worldwide. Approximately 5% of the general population is colonised with the pathogen, but most are protected from disease by normal intestinal flora or immune responses to toxins. We developed a stochastic compartmental model of CDI in hospitals that captures the condition of the host's gut flora and the role of adaptive immune responses. A novel, derivative-based method for sensitivity analysis of individual-level outcomes was developed and applied to the model. The model reproduced the observed incidence and recurrence rates for hospitals with high and moderate incidence of hospital-acquired CDI. In both scenarios, the reproduction number for within-hospital transmission was less than 1 (0.67 and 0.44, respectively), but the proportion colonised with C. difficile at discharge (7.3 and 6.1%, respectively) exceeded the proportion colonised at admission (5%). The transmission and prevalence of CDI were most sensitive to the average length of stay and the transmission rate of the pathogen. Recurrent infections were most strongly affected by the treatment success rate and the immune profile of patients. Transmission within hospitals is substantial and leads to a net export of colonised individuals to the broader community. However, within-hospital transmission alone is insufficient to sustain endemic conditions in hospitals without the constant importation of colonised individuals. Improved hygiene practices to reduce transmission from symptomatic and asymptomatic individuals and reduced length of stay are most likely to reduce within-hospital transmission and infections; however, these interventions are likely to have a smaller effect on the probability of recurrence. Immunising inpatients against the toxins produced by C. difficile will reduce the incidence of CDI but may increase transmission.

The effect of Wolbachia on dengue outbreaks when dengue is repeatedly introduced.

Use of the Wolbachia bacterium is a proposed new strategy to reduce dengue transmission, which results in around 390 million individuals infected annually. In places with strong variations in climatic conditions such as temperature and rainfall, dengue epidemics generally occur only at a certain time of the year. Where dengue is not endemic, the time of year in which imported cases enter the population plays a crucial role in determining the likelihood of outbreak occurrence. We use a mathematical model to study the effects of Wolbachia on dengue transmission dynamics and dengue seasonality. We focus in regions where dengue is not endemic but can spread due to the presence of a dengue vector and the arrival of people with dengue on a regular basis. Our results show that the time-window in which outbreaks can occur is reduced in the presence of Wolbachia-carrying Aedes aegypti mosquitoes by up to six weeks each year. We find that Wolbachia reduces overall case numbers by up to 80%. The strongest effect is obtained when the amplitude of the seasonal forcing is low (0.02-0.30). The benefits of Wolbachia also depend on the transmission rate, with the bacteria most effective at moderate transmission rates ranging between 0.08-0.12. Such rates are consistent with fitted estimates for Cairns, Australia.