Josephine G. Walker

“One Health” or Three? Publication Silos Among the One Health Disciplines

The One Health initiative is a global effort fostering interdisciplinary collaborations to address challenges in human, animal, and environmental health. While One Health has received considerable press, its benefits remain unclear because its effects have not been quantitatively described. We systematically surveyed the published literature and used social network analysis to measure interdisciplinarity in One Health studies constructing dynamic pathogen transmission models. The number of publications fulfilling our search criteria increased by 14.6% per year, which is faster than growth rates for life sciences as a whole and for most biology subdisciplines. Surveyed publications clustered into three communities: one used by ecologists, one used by veterinarians, and a third diverse-authorship community used by population biologists, mathematicians, epidemiologists, and experts in human health. Overlap between these communities increased through time in terms of author number, diversity of co-author affiliations, and diversity of citations. However, communities continue to differ in the systems studied, questions asked, and methods employed. While the infectious disease research community has made significant progress toward integrating its participating disciplines, some segregation—especially along the veterinary/ecological research interface—remains.

Generalists at the interface: Nematode transmission between wild and domestic ungulates

Highlights • Nematodes vary in host range, affecting potential for cross-species transmission.• Host-specific parasites account for <50% of the parasite species infecting a host.• Goats are most and horses are least liable to nematodes carried by wildlife.• Plains zebra and mouflon are most liable to nematodes carried by livestock.• Existing knowledge is biased, 84% of references are from Africa, Europe, North America.

Uncertain links in host-parasite networks: lessons for parasite transmission in a multi-host system

For many parasites, the full set of hosts that are susceptible to infection is not known, and this could lead to a bias in estimates of transmission. We used counts of individual adult parasites from historical parasitology studies in southern Africa to map a bipartite network of the nematode parasites of herbivore hosts that occur in Botswana. Bipartite networks are used in community ecology to represent interactions across trophic levels. We used a Bayesian hierarchical model to predict the full set of host–parasite interactions from existing data on parasitic gastrointestinal nematodes of wild and domestic ungulates given assumptions about the distribution of parasite counts within hosts, while accounting for the relative uncertainty of less sampled species. We used network metrics to assess the difference between the observed and predicted networks, and to explore the connections between hosts via their shared parasites using a host–host unipartite network projected from the bipartite network. The model predicts a large number of missing links and identifies red hartebeest, giraffe and steenbok as the hosts that have the most uncertainty in parasite diversity. Further, the unipartite network reveals clusters of herbivores that have a high degree of parasite sharing, and these clusters correspond closely with phylogenetic distance rather than with the wild/domestic boundary. These results provide a basis for predicting the risk of cross-species transmission of nematode parasites in areas where livestock and wildlife share grazing land. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’.

New media methods for syndromic surveillance and disease modelling

Morbidity and mortality associated with an infectious disease outbreak can be mitigated by early detection followed by swift action. Modelling, tracking and predicting disease outbreaks are therefore priorities for public health agencies. New media data sources, including social media platforms, the internet and mobile phone applications, now aid in detecting outbreaks earlier than would have been possible using traditional surveillance methods alone. I review the literature on uses of new media methods for detecting disease outbreaks in humans and animals, with a focus on veterinary diseases and the difference in challenges compared with human disease surveillance. I then discuss the complex issue of evaluation of new media-based surveillance systems. The proliferation of new media methods for disease surveillance has not included published evaluation of each method or of the challenges faced, which limits the potential for a particular method to be applied outside its original context.

Mixed methods evaluation of targeted selective anthelmintic treatment by resource-poor smallholder goat farmers in Botswana

Graphical abstract

Estimating the contribution of key populations towards the spread of HIV in Dakar, Senegal

Key populations including female sex workers (FSW) and men who have sex with men (MSM) bear a disproportionate burden of HIV. However, the role of focusing prevention efforts on these groups for reducing a countrys HIV epidemic is debated. We estimate the extent to which HIV transmission among FSW and MSM contributes to overall HIV transmission in Dakar, Senegal, using a dynamic assessment of the population attributable fraction (PAF).

Prediction and attenuation of seasonal spillover of parasites between wild and domestic ungulates in an arid mixed‐use system

Abstract Transmission of parasites between host species affects host population dynamics, interspecific competition, and ecosystem structure and function. In areas where wild and domestic herbivores share grazing land, management of parasites in livestock may affect or be affected by sympatric wildlife due to cross‐species transmission. We develop a novel method for simulating transmission potential based on both biotic and abiotic factors in a semi‐arid system in Botswana. Optimal timing of antiparasitic treatment in livestock is then compared under a variety of alternative host scenarios, including seasonally migrating wild hosts. In this region, rainfall is the primary driver of seasonality of transmission, but wildlife migration leads to spatial differences in the effectiveness of treatment in domestic animals. Additionally, competent migratory wildlife hosts move parasites across the landscape. Simulated transmission potential matches observed patterns of clinical disease in livestock in the study area. Increased wildlife contact is correlated with a decrease in disease, suggesting that non‐competent wild hosts may attenuate transmission by removing infective parasite larvae from livestock pasture. Optimising the timing of treatment according to within‐year rainfall patterns was considerably more effective than treating at a standard time of year. By targeting treatment in this way, efficient control can be achieved, mitigating parasite spillover from wildlife where it does occur. Synthesis and applications. This model of parasite transmission potential enables evidence‐based management of parasite spillover between wild and domestic species in a spatio‐temporally dynamic system. It can be applied in other mixed‐use systems to mitigate parasite transmission under altered climate scenarios or changes in host ranges.

Interim impact evaluation of the hepatitis C virus elimination program in Georgia

Background and Aims Georgia has one of the highest hepatitis C virus (HCV) prevalence rates in the world, with >5% of the adult population (~150,000 people) chronically infected. In April 2015, the Georgian government, in collaboration with CDC and other partners, launched a national program to eliminate HCV through scaling up HCV treatment and prevention interventions, with the aim of achieving a 90% reduction in prevalence by 2020. We evaluate the interim impact of the HCV treatment program as of 31 October 2017, and assess the feasibility of achieving the elimination goal by 2020. Method We developed a dynamic HCV transmission model to capture the current and historical epidemic dynamics of HCV in Georgia, including the main drivers of transmission. Using the 2015 national sero-survey and prior surveys conducted among people who inject drugs (PWID) from 1997-2015, the model was calibrated to data on HCV prevalence by age, gender and PWID status, and the age distribution of PWID. We use the model to project the interim impact of treatment strategies currently being undertaken as part of the ongoing Georgia HCV elimination program, while accounting for treatment failure/loss to follow up, in order to determine whether they are on track to achieving their HCV elimination target by 2020, or whether strategies need to be modified to ensure success. Results A treatment rate of 2,050 patients/month was required from the beginning of the national program to achieve a 90% reduction in prevalence by the end of 2020, with equal treatment rates of PWID and the general population. From May 2015 to October 2017, 40,420 patients were treated, an average of ~1,350 per month; although the treatment rate has recently declined from a peak of 4,500/month in September 2016 to 2100/month in November-December 2016, and 1000/month in August-October 2017, with a sustained virological response rate (SVR) of 98% per-protocol or 78% intent to treat. The model projects that the treatments undertaken up to October 2017 have reduced adult chronic prevalence by 26% (18-35%) to 3.7% (2.9-5.1%), reduced total incidence by 25% (15-35%), and prevented 1845 (751-3969) new infections and 93 (31-177) HCV-related deaths. If the treatment rate of 1000 patients initiated per month continues, prevalence will have halved by 2020, and reduce by 90% by 2026. In order to reach a 90% reduction by 2020, the treatment rate must increase 3.5-fold to 4000/month. Conclusion The Georgia HCV elimination program has accomplished an impressive scale up of treatment, which has already impacted on prevalence and incidence, and averted deaths due to HCV. However, extensive scale up is needed to achieve a 90% reduction in prevalence by 2020.

A mechanistic hydro-epidemiological model of liver fluke risk

The majority of existing models for predicting disease risk in response to climate change are empirical. These models exploit correlations between historical data, rather than explicitly describing relationships between cause and response variables. Therefore, they are unsuitable for capturing impacts beyond historically observed variability and have limited ability to guide interventions. In this study, we integrate environmental and epidemiological processes into a new mechanistic model, taking the widespread parasitic disease of fasciolosis as an example. The model simulates environmental suitability for disease transmission at a daily time step and 25 m resolution, explicitly linking the parasite life cycle to key weather–water–environment conditions. Using epidemiological data, we show that the model can reproduce observed infection levels in time and space for two case studies in the UK. To overcome data limitations, we propose a calibration approach combining Monte Carlo sampling and expert opinion, which allows constraint of the model in a process-based way, including a quantification of uncertainty. The simulated disease dynamics agree with information from the literature, and comparison with a widely used empirical risk index shows that the new model provides better insight into the time–space patterns of infection, which will be valuable for decision support.

Curbing the hepatitis C virus epidemic in Pakistan: the impact of scaling up treatment and prevention for achieving elimination

Abstract Background The World Health Organization (WHO) has developed a global health strategy to eliminate viral hepatitis. We project the treatment and prevention requirements to achieve the WHO HCV elimination target of reducing HCV incidence by 80% and HCV-related mortality by 65% by 2030 in Pakistan, which has the second largest HCV burden worldwide. Methods We developed an HCV transmission model for Pakistan, and calibrated it to epidemiological data from a national survey (2007), surveys among people who inject drugs (PWID), and blood donor data. Current treatment coverage data came from expert opinion and published reports. The model projected the HCV burden, including incidence, prevalence and deaths through 2030, and estimated the impact of varying prevention and direct-acting antiviral (DAA) treatment interventions necessary for achieving the WHO HCV elimination targets. Results With no further treatment (currently ∼150 000 treated annually) during 2016–30, chronic HCV prevalence will increase from 3.9% to 5.1%, estimated annual incident infections will increase from 700 000 to 1 100 000, and 1 400 000 HCV-associated deaths will occur. To reach the WHO HCV elimination targets by 2030, 880 000 annual DAA treatments are required if prevention is not scaled up and no treatment prioritization occurs. By targeting treatment toward persons with cirrhosis (80% treated annually) and PWIDs (double the treatment rate of non-PWIDs), the required annual treatment number decreases to 750 000. If prevention activities also halve transmission risk, this treatment number reduces to 525 000 annually. Conclusions Substantial HCV prevention and treatment interventions are required to reach the WHO HCV elimination targets in Pakistan, without which Pakistan’s HCV burden will increase markedly.