The potential distribution of Bacillus anthracis suitability across Uganda using INLA.

To reduce the veterinary, public health, environmental, and economic burden associated with anthrax outbreaks, it is vital to identify the spatial distribution of areas suitable for Bacillus anthracis, the causative agent of the disease. Bayesian approaches have previously been applied to estimate uncertainty around detected areas of B. anthracis suitability. However, conventional simulation-based techniques are often computationally demanding. To solve this computational problem, we use Integrated Nested Laplace Approximation (INLA) which can adjust for spatially structured random effects, to predict the suitability of B. anthracis across Uganda. We apply a Generalized Additive Model (GAM) within the INLA Bayesian framework to quantify the relationships between B. anthracis occurrence and the environment. We consolidate a national database of wildlife, livestock, and human anthrax case records across Uganda built across multiple sectors bridging human and animal partners using a One Health approach. The INLA framework successfully identified known areas of species suitability in Uganda, as well as suggested unknown hotspots across Northern, Eastern, and Central Uganda, which have not been previously identified by other niche models. The major risk factors for B. anthracis suitability were proximity to water bodies (0-0.3 km), increasing soil calcium (between 10 and 25 cmolc/kg), and elevation of 140-190 m. The sensitivity of the final model against the withheld evaluation dataset was 90% (181 out of 202 = 89.6%; rounded up to 90%). The prediction maps generated using this model can guide future anthrax prevention and surveillance plans by the relevant stakeholders in Uganda.

Dynamics and risk of transmission of bovine tuberculosis in the emerging dairy regions of Ethiopia.

The Ethiopian government has several initiatives to expand and intensify the dairy industry; however, the risk of bovine tuberculosis (bTB) spread is a challenge. To assess the rate of expansion and risk factors for transmission of bTB within-herds, we carried out a repeated cross-sectional survey at two time points, 2016/17 and 2018, in three regional cities, namely, Gondar, Hawassa and Mekelle, representing the emerging dairy belts of Ethiopia. The total number of herds involved was 128, comprising an average of 2303 cattle in each round. The Single Intradermal Comparative Cervical Tuberculin (SICCT) test was used to identify reactor status and data on herd-level risk factors were collected using a structured questionnaire. In the first survey, the apparent prevalence of bTB, as measured by the SICCT test, was 4.5% (95% CI 3.7-5.4%) at the individual animal-level and 24% (95% CI 17.5-32%) at the herd-level. There was no statistically significant change in the overall apparent prevalence or regional distribution at the second survey, consistent with the infection being endemic. The incidence rate was estimated at 3.6 (95% CI 2.8-4.5) and 6.6 (95% CI 3.0-12.6) cases/100 cattle (or herd)-years at the animal- and herd-levels, respectively. Risk factors significantly associated with the within-herd transmission of bTB were age group and within-herd apparent prevalence at the start of the observation period. We noted that farmers voluntarily took steps to remove reactor cattle from their herds as a consequence of the information shared after the first survey. Removal of reactors between surveys was associated with a reduced risk of transmission within these herds. However, with no regulatory barriers to the sale of reactor animals, such actions could potentially lead to further spread between herds. We therefore advocate the importance of setting up regulations and then establishing a systematic bTB surveillance programme to monitor the impact prior to implementing any control measures in Ethiopia.

Modelling norovirus transmission and vaccination.

BACKGROUND: Norovirus is thought to be responsible for a fifth of all acute gastroenteritis cases globally each year. The population level transmission dynamics of this very common virus are still poorly understood, in part because illness is under-reported. With vaccines undergoing clinical trials, there is a growing need for appropriate, empirically grounded models, to predict the likely impact of vaccination. METHODS: We developed a dynamic age-specific mathematical model of norovirus transmission and vaccination, informed by available data, particularly age-stratified time series case notification data. We introduce the use of a self-reporting Markov model to account for variation by age and over time in the statutory reporting of norovirus in Germany. We estimated the model using a sequential Monte Carlo particle filter. We then extended and applied our estimated model to investigate the potential impact of a range of immunisation strategies. We performed sensitivity analyses on the mode of vaccine action and other vaccine-related parameters. RESULTS: We find that routine immunisation could reduce the incidence of norovirus by up to 70.5% even when those vaccines do not provide complete protection from disease. Furthermore, we find that the relative efficiency of alternative strategies targeting different age groups are dependant on the outcome we consider and are sensitive to assumptions on the mode of vaccine action. Strategies that target infants and toddler are more efficient in preventing infection but targeting older adults is preferable for preventing severe outcomes. CONCLUSIONS: Our model provides a robust estimate of a dynamic transmission model for norovirus at the population level. Vaccination may be an effective strategy in preventing disease but further work is required to ascertain norovirus vaccine efficacy, its mode of action and to estimate the cost-effectiveness of immunisation against norovirus.

Norovirus transmission dynamics: a modelling review.

Norovirus is one of the leading causes of viral gastroenteritis worldwide and responsible for substantial morbidity, mortality and healthcare costs. To further understanding of the epidemiology and control of norovirus, there has been much recent interest in describing the transmission dynamics of norovirus through mathematical models. In this study, we review the current modelling approaches for norovirus transmission. We examine the data and methods used to estimate these models that vary structurally and parametrically between different epidemiological contexts. Many of the existing studies at population level have focused on the same case notification dataset, whereas models from outbreak settings are highly specific and difficult to generalise. In this review, we explore the consistency in the description of norovirus transmission dynamics and the robustness of parameter estimates between studies. In particular, we find that there is considerable variability in estimates of key parameters such as the basic reproduction number, which may mean that the effort required to control norovirus at the population level may currently be underestimated.

Recurrence of bovine tuberculosis breakdowns in Great Britain: risk factors and prediction.

Bovine tuberculosis (bTB) is an important economic disease worldwide with implications for both animal and human health. In Great Britain the number of herds that test positive for bTB, termed "breakdowns", has increased over the last two decades. Despite more intensive testing during a breakdown, around 23% of breakdowns recur within 12 months of the previous breakdown ending, and around 38% within 24 months. These "recurrent" breakdowns may be important for onward transmission of infection. Detailed case-control data were analysed to identify factors associated with recurrence within 12 months. The model predicted 83% of all recurrent breakdowns, with a positive predictive value (PPV) of 44%. A further model, restricted to data currently available nationally, was not sufficient to predict recurrence reliably; at a sensitivity of 72-76%, the PPV was 33-36%, when validated on independent data. Factors identified to be associated with recurrence are consistent with previous studies; namely, the number of reactors, a recent bTB history in the herd and a lack of association with the confirmation status of the initial breakdown. These variables are indicative of a higher level of infection or residual infection, and could be useful in the future development of predictive models for bTB recurrence.

Measuring social networks in British primary schools through scientific engagement.

Primary schools constitute a key risk group for the transmission of infectious diseases, concentrating great numbers of immunologically naive individuals at high densities. Despite this, very little is known about the social patterns of mixing within a school, which are likely to contribute to disease transmission. In this study, we present a novel approach where scientific engagement was used as a tool to access school populations and measure social networks between young (4-11 years) children. By embedding our research project within enrichment activities to older secondary school (13-15) children, we could exploit the existing links between schools to achieve a high response rate for our study population (around 90% in most schools). Social contacts of primary school children were measured through self-reporting based on a questionnaire design, and analysed using the techniques of social network analysis. We find evidence of marked social structure and gender assortativity within and between classrooms in the same school. These patterns have been previously reported in smaller studies, but to our knowledge no study has attempted to exhaustively sample entire school populations. Our innovative approach facilitates access to a vitally important (but difficult to sample) epidemiological sub-group. It provides a model whereby scientific communication can be used to enhance, rather than merely complement, the outcomes of research.

Predicting prolonged bovine tuberculosis breakdowns in Great Britain as an aid to control.

Bovine tuberculosis (bTB) is an important notifiable disease in cattle in Great Britain (GB), and is subject to statutory control measures. Despite this, disease incidence has increased since the mid-1980s, and around 30% of herd breakdowns continue for more than 240 days. This is twice the shortest possible time for confirmed breakdowns to test clear from infection (≈120 days), and four times the shortest possible time for unconfirmed breakdowns (≈60 days). These "prolonged" breakdowns consume substantial resources and may act as an ongoing source of infection. It is not clear why some breakdowns become prolonged. Existing detailed case-control data have been re-analysed to determine risk factors for breakdowns lasting longer than 240 days, the strongest of which was the confirmation status of the breakdown: OR 12.6 (95%CI: 6.7-25.4). A further model restricted to data available early on in a breakdown for all breakdowns nationally, can predict 82-84% of prolonged breakdowns with a positive predictive value of 44-49% when validated using existing national datasets over a 4-year period. Identification of prolonged breakdowns at an earlier stage could help to target bTB controls in GB.

Time is of the essence: exploring a measles outbreak response vaccination in Niamey, Niger.

The current World Health Organization recommendations for response during measles epidemics focus on case management rather than outbreak response vaccination (ORV) campaigns, which may occur too late to impact morbidity and mortality and have a high cost per case prevented. Here, we explore the potential impact of an ORV campaign conducted during the 2003-2004 measles epidemic in Niamey, Niger. We measured the impact of this intervention and also the potential impact of alternative strategies. Using a unique geographical, epidemiologic and demographic dataset collected during the epidemic, we developed an individual-based simulation model. We estimate that a median of 7.6% [4.9-8.9] of cases were potentially averted as a result of the outbreak response, which vaccinated approximately 57% (84563 of an estimated 148600) of children in the target age range (6-59 months), 23 weeks after the epidemic started. We found that intervening early (up to 60 days after the start of the epidemic) and expanding the age range to all children aged 6 months to 15 years may lead to a much larger (up to 90%) reduction in the number of cases in a West African urban setting like Niamey. Our results suggest that intervening earlier even with lower target coverage (approx. 60%), but a wider age range, may be more effective than intervening later with high coverage (more than 90%) in similar settings. This has important implications for the implementation of reactive vaccination interventions as they can be highly effective if the response is fast with respect to the spread of the epidemic.