No abstract

A Bayesian approach was developed by Hald et al.((1)) to estimate the contribution of different food sources to the burden of human salmonellosis in Denmark. This article describes the development of several modifications that can be used to adapt the model to different countries and pathogens. Our modified Hald model has several advantages over the original approach, which include the introduction of uncertainty in the estimates of source prevalence and an improved strategy for identifiability. We have applied our modified model to the two major food-borne zoonoses in New Zealand, namely, campylobacteriosis and salmonellosis. Major challenges were the data quality for salmonellosis and the inclusion of environmental sources of campylobacteriosis. We conclude that by modifying the Hald model we have improved its identifiability, made it more applicable to countries with less intensive surveillance, and feasible for other pathogens, in particular with respect to the inclusion of nonfood sources. The wider application and better understanding of this approach is of particular importance due to the value of the model for decision making and risk management.

The epidemiology of human campylobacteriosis is complex but in recent years understanding of this disease has advanced considerably. Despite being a major public health concern in many countries, the presence of multiple hosts, genotypes and transmission pathways has made it difficult to identify and quantify the determinants of human infection and disease. This has delayed the development of successful intervention programmes for this disease in many countries including New Zealand, a country with a comparatively high, yet until recently poorly understood, rate of notified disease. This study investigated the epidemiology of Campylobacter jejuni at the genotype-level over a 3-year period between 2005 and 2008 using multilocus sequence typing. By combining epidemiological surveillance and population genetics, a dominant, internationally rare strain of C. jejuni (ST474) was identified, and most human cases (65.7%) were found to be caused by only seven different genotypes. Source association of genotypes was used to identify risk factors at the genotype-level through multivariable logistic regression and a spatial model. Poultry-associated cases were more likely to be found in urban areas compared to rural areas. In particular young children in rural areas had a higher risk of infection with ruminant strains than their urban counterparts. These findings provide important information for the implementation of pathway-specific control strategies.

Background International and global organisations advocate targeting interventions to areas of high HIV prevalence (ie, hotspots). To better understand the potential benefits of geo-targeted control, we assessed the extent to which HIV hotspots along Lake Victoria sustain transmission in neighbouring populations in south-central Uganda. Methods We did a population-based survey in Rakai, Uganda, using data from the Rakai Community Cohort Study. The study surveyed all individuals aged 15-49 years in four high-prevalence Lake Victoria fishing communities and 36 neighbouring inland communities. Viral RNA was deep sequenced from participants infected with HIV who were antiretroviral therapy-naive during the observation period. Phylogenetic analysis was used to infer partial HIV transmission networks, including direction of transmission. Reconstructed networks were interpreted through data for current residence and migration history. HIV transmission flows within and between high-prevalence and low-prevalence areas were quantified adjusting for incomplete sampling of the population. Findings Between Aug 10, 2011, and Jan 30, 2015, data were collected for the Rakai Community Cohort Study. 25 882 individuals participated, including an estimated 75•7% of the lakeside population and 16•2% of the inland population in the Rakai region of Uganda. 5142 participants were HIV-positive (2703 [13•7%] in inland and 2439 [40•1%] in fishing communities). 3878 (75•4%) people who were HIV-positive did not report antiretroviral therapy use, of whom 2652 (68•4%) had virus deep-sequenced at sufficient quality for phylogenetic analysis. 446 transmission networks were reconstructed, including 293 linked pairs with inferred direction of transmission. Adjusting for incomplete sampling, an estimated 5•7% (95% credibility interval 4•4-7•3) of transmissions occurred within lakeside areas, 89•2% (86•0-91•8) within inland areas, 1•3% (0•6-2•6) from lakeside to inland areas, and 3•7% (2•3-5•8) from inland to lakeside areas. Interpretation Cross-community HIV transmissions between Lake Victoria hotspots and surrounding inland populations are infrequent and when they occur, virus more commonly flows into rather than out of hotspots. This result suggests that targeted interventions to these hotspots will not alone control the epidemic in inland populations, where most transmissions occur. Thus, geographical targeting of high prevalence areas might not be effective for broader epidemic control depending on underlying epidemic dynamics.