One Health drivers of antibacterial resistance: Quantifying the relative impacts of human, animal and environmental use and transmission

This is the final version. Available on open access from Elsevier via the DOI in this recordData accessibility statement: All model code is open source and available for download on GitHub https://github.com/rdbooton/OHDARTmodelObjectives Antibacterial resistance (ABR) is a major global health security threat, with a disproportionate burden on lower-and middle-income countries (LMICs). It is not understood how ‘One Health’, where human health is co-dependent on animal health and the environment, might impact the burden of ABR in LMICs. Thailand's 2017 “National Strategic Plan on Antimicrobial Resistance” (NSP-AMR) aims to reduce AMR morbidity by 50% through 20% reductions in human and 30% in animal antibacterial use (ABU). There is a need to understand the implications of such a plan within a One Health perspective. Methods A model of ABU, gut colonisation with extended-spectrum beta-lactamase (ESBL)-producing bacteria and transmission was calibrated using estimates of the prevalence of ESBL-producing bacteria in Thailand. This model was used to project the reduction in human ABR over 20 years (2020–2040) for each One Health driver, including individual transmission rates between humans, animals and the environment, and to estimate the long-term impact of the NSP-AMR intervention. Results The model predicts that human ABU was the most important factor in reducing the colonisation of humans with resistant bacteria (maximum 65.7–99.7% reduction). The NSP-AMR is projected to reduce human colonisation by 6.0–18.8%, with more ambitious targets (30% reductions in human ABU) increasing this to 8.5–24.9%. Conclusions Our model provides a simple framework to explain the mechanisms underpinning ABR, suggesting that future interventions targeting the simultaneous reduction of transmission and ABU would help to control ABR more effectively in Thailand.Antimicrobial Resistance Cross Council Initiativ

Predicted Impact of COVID-19 on Neglected Tropical Disease Programs and the Opportunity for Innovation

Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.</p

Analysis of 2009 pandemic influenza A/H1N1 outcomes in 19 European countries: association with completeness of national strategic plans

Objective: To describe changes in reported influenza activity associated with the 2009 H1N1 pandemic in European countries and determine whether there is a correlation between these changes and completeness of national strategic pandemic preparedness. Design: A retrospective correlational study. Setting: Countries were included if their national strategic plans had previously been analysed and if weekly influenza-like illness (ILI) data from sentinel networks between week 21, 2006 and week 20, 2010 were more than 50% complete. Outcome measures: For each country we calculated three outcomes: the percentage change in ILI peak height during the pandemic relative to the prepandemic mean; the timing of the ILI peak and the percentage change in total cases relative to the prepandemic mean. Correlations between these outcomes and completeness of a country's national strategic pandemic preparedness plan were assessed using the Pearson product-moment correlation coefficient. Results: Nineteen countries were included. The ILI peak occurred earlier than the mean seasonal peak in 17 countries. In 14 countries the pandemic peak was higher than the seasonal peak, though the difference was large only in Norway, the UK and Greece. Nine countries experienced more total ILI cases during the pandemic compared with the mean for prepandemic years. Five countries experienced two distinct pandemic peaks. There was no clear pattern of correlation between overall completeness of national strategic plans and pandemic influenza outcome measures and no evidence of association between these outcomes and components of pandemic plans that might plausibly affect influenza outcomes ( public health interventions, vaccination, antiviral use, public communication). Amongst the 17 countries with a clear pandemic peak, only the correlation between planning for essential services and change in total ILI cases significantly differed from zero: correlation coefficient (95% CI) 0.50 (0.02, 0.79). Conclusions: The diversity of pandemic influenza outcomes across Europe is not explained by the marked variation in the completeness of pandemic plans

Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza

Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups, but there is considerable uncertainty as to the essential mechanisms and their parametrization. In this paper, we identify a number of characteristic features of influenza incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. By constraining the output of simple models to match these characteristic features, we investigate the role played by population heterogeneity, multiple strains, cross-immunity and the rate of strain evolution in the generation of incidence time series. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match observed time-series data. Our work gives estimates of the seasonal peak basic reproduction number, R0, in the range 1.6–3. Estimates of R0 are strongly correlated with the timescale for waning of immunity to current circulating seasonal influenza strain, which we estimate is between 3 and 8 years. Seasonal variation in transmissibility is largely confined to 15–30% of its mean value. While population heterogeneity and cross-immunity are required mechanisms, the degree of heterogeneity and cross-immunity is not tightly constrained. We discuss our findings in the context of other work fitting to seasonal influenza data

Seasonal Influenza Vaccination for Children in Thailand: A Cost-Effectiveness Analysis

10.1371/journal.pmed.1001829PLoS Medicine125e100182

Seasonal influenza vaccination for children in Thailand: a cost-effectiveness analysis.

BACKGROUND: Seasonal influenza is a major cause of mortality worldwide. Routine immunization of children has the potential to reduce this mortality through both direct and indirect protection, but has not been adopted by any low- or middle-income countries. We developed a framework to evaluate the cost-effectiveness of influenza vaccination policies in developing countries and used it to consider annual vaccination of school- and preschool-aged children with either trivalent inactivated influenza vaccine (TIV) or trivalent live-attenuated influenza vaccine (LAIV) in Thailand. We also compared these approaches with a policy of expanding TIV coverage in the elderly. METHODS AND FINDINGS: We developed an age-structured model to evaluate the cost-effectiveness of eight vaccination policies parameterized using country-level data from Thailand. For policies using LAIV, we considered five different age groups of children to vaccinate. We adopted a Bayesian evidence-synthesis framework, expressing uncertainty in parameters through probability distributions derived by fitting the model to prospectively collected laboratory-confirmed influenza data from 2005-2009, by meta-analysis of clinical trial data, and by using prior probability distributions derived from literature review and elicitation of expert opinion. We performed sensitivity analyses using alternative assumptions about prior immunity, contact patterns between age groups, the proportion of infections that are symptomatic, cost per unit vaccine, and vaccine effectiveness. Vaccination of children with LAIV was found to be highly cost-effective, with incremental cost-effectiveness ratios between about 2,000 and 5,000 international dollars per disability-adjusted life year averted, and was consistently preferred to TIV-based policies. These findings were robust to extensive sensitivity analyses. The optimal age group to vaccinate with LAIV, however, was sensitive both to the willingness to pay for health benefits and to assumptions about contact patterns between age groups. CONCLUSIONS: Vaccinating school-aged children with LAIV is likely to be cost-effective in Thailand in the short term, though the long-term consequences of such a policy cannot be reliably predicted given current knowledge of influenza epidemiology and immunology. Our work provides a coherent framework that can be used for similar analyses in other low- and middle-income countries

Contact mixing patterns and population movement among migrant workers in an urban setting in Thailand

Data relating to contact mixing patterns among humans are essential for the accurate modeling of infectious disease transmission dynamics. Here, we describe contact mixing patterns among migrant workers in urban settings in Thailand, based on a survey of 369 migrant workers of three nationalities. Respondents recorded their demographic data, including age, sex, nationality, workplace, income, and education. Each respondent chose a single day to record their contacts; this resulted in a total of more than 8300 contacts. The characteristics of contacts were recorded, including their age, sex, nationality, location of contact, and occurrence of physical contact. More than 75% of all contacts occurred among migrants aged 15 to 39 years. The contacts were highly clustered in this age group among migrant workers of all three nationalities. There were far fewer contacts between migrant workers with younger and older age groups. The pattern varied slightly among different nationalities, which was mostly dependent upon the types of jobs taken. Half of migrant workers always returned to their home country at most once a year and on a seasonal basis. The present study has helped us gain a better understanding of contact mixing patterns among migrant workers in urban settings. This information is useful both when simulating disease epidemics and for guiding optimal disease control strategies among this vulnerable section of the population