Effects of regional differences and demography in modelling foot-and-mouth disease in cattle at the national scale

Foot-and-mouth disease (FMD) is a fast-spreading viral infection that can produce large and costly outbreaks in livestock populations. Transmission occurs at multiple spatial scales, as can the actions used to control outbreaks. The US cattle industry is spatially expansive, with heterogeneous distributions of animals and infrastructure. We have developed a model that incorporates the effects of scale for both disease transmission and control actions, applied here in simulating FMD outbreaks in US cattle. We simulated infection initiating in each of the 3049 counties in the contiguous US, 100 times per county. When initial infection was located in specific regions, large outbreaks were more likely to occur, driven by infrastructure and other demographic attributes such as premises clustering and number of cattle on premises. Sensitivity analyses suggest these attributes had more impact on outbreak metrics than the ranges of estimated disease parameter values. Additionally, although shipping accounted for a small percentage of overall transmission, areas receiving the most animal shipments tended to have other attributes that increase the probability of large outbreaks. The importance of including spatial and demographic heterogeneity in modelling outbreak trajectories and control actions is illustrated by specific regions consistently producing larger outbreaks than others

Estimating the impact and economic trade-offs of infectious disease control strategies using metapopulation models

Infectious diseases remain the main cause of death in low-income countries. Because of this, efforts to control the circulation of infectious agents are a priority for public policy makers. This control is challenged by a combination of complex disease dynamics, funding constraints or lack of political and societal commitment. These challenges are generally heterogeneous between geographical settings making the impact of control strategies hard to assess. In view of this, the purpose of this research is to integrate economic and epidemiological tools in order to improve support for disease control planning and implementation. To do this, I develop a metapopulation model framework to analyse the impact of control strategies when there are neighbouring populations with different epidemiological conditions. The results from this framework can be incorporated into further economic analysis and optimisations. The first section of this project aims to understand interventions’ effects when transmission intensity varies between populations. As a first approach, I implement the framework to analyse indirect effects of interventions for a transmission-stratified population, using generic models. Then, to contextualise the findings from the generic model, I analyse optimal intervention allocation for malaria control. Results from this section evidenced the importance of aligning local and global control strategies. The second section of this project focuses on understanding the consequences of disease control when intervention uptake varies between populations. For this, the metapopulation framework is applied to estimate the burden populations undergo due to the presence of an anti-vaccination movement. First, I analyse the burden of an outbreak of a vaccine preventable disease in a population where there are opposing vaccine acceptance views, implementing a measles transmission. Finally, I use the same approach to estimate the likely impact of vaccine hesitancy on the control of the COVID-19 pandemic. Results of this section highlight the importance of addressing vaccine hesitancy as a public health priorityOpen Acces

Cost-benefit analysis of foot and mouth disease control in Ethiopia

Foot and mouth disease (FMD) occurs endemically in Ethiopia. Quantitative insights on its national economic impact and on the costs and benefits of control options are, however, lacking to support decision making in its control. The objectives of this study were, therefore, to estimate the annual costs of FMD in cattle production systems of Ethiopia, and to conduct an ex ante cost-benefit analysis of potential control alternatives.<br/><br/>The annual costs of FMD were assessed based on production losses, export losses and control costs. The total annual costs of FMD under the current status quo of no official control program were estimated at 1354 (90% CR: 864–2042) million birr. The major cost (94%) was due to production losses. The costs and benefits of three potential control strategies: 1) ring vaccination (reactive vaccination around outbreak area supported by animal movement restrictions, 2) targeted vaccination (annual preventive vaccination in high risk areas plus ring vaccination in the rest of the country), and 3) preventive mass vaccination (annual preventive vaccination of the whole national cattle population) were compared with the baseline scenario of no official control program. Experts were elicited to estimate the influence of each of the control strategies on outbreak incidence and number of cases per outbreak. Based on these estimates, the incidence of the disease was simulated stochastically for 10 years. Preventive mass vaccination was epidemiologically the most efficient control strategy by reducing the national outbreak incidence below 5% with a median time interval of 3 years, followed by targeted vaccination strategy with a corresponding median time interval of 5 years. On average, all evaluated control strategies resulted in positive net present values. The ranges in the net present values were, however, very wide, including negative values. The targeted vaccination strategy was the most economic strategy with a median benefit cost ratio of 4.29 (90%CR: 0.29–9.63). It was also the least risky strategy with 11% chance of a benefit cost ratio of less than one.<br/><br/>The study indicates that FMD has a high economic impact in Ethiopia. Its control is predicted to be economically profitable even without a full consideration of gains from export. The targeted vaccination strategy is shown to provide the largest economic return with a relatively low risk of loss. More studies to generate data, especially on production impact of the disease and effectiveness of control measures are needed to improve the rigor of future analysis.<br/

Operations research in disaster preparedness and response: The public health perspective

Operations research is the scientific study of operations for the purpose of better decision making and management. Disasters are defined as events whose consequences exceed the capability of civil protection and public health systems to provide necessary responses in a timely manner. Public health science is applied to the design of operations of public health services and therefore operations research principles and techniques can be applied in public health. Disaster response quantitative methods such as operations research addressing public health are important tools for planning effective responses to disasters. Models address a variety of decision makers (e.g. first responders, public health officials), geographic settings, strategies modelled (e.g. dispensing, supply chain network design, prevention or mitigation of disaster effects, treatment) and outcomes evaluated (costs, morbidity, mortality, logistical outcomes) and use a range of modelling methodologies. Regarding natural disasters the modelling approaches have been rather limited. Response logistics related to public health impact of disasters have been modelled more intensively since decisions about procurement, transport, stockpiling, and maintenance of needed supplies but also mass vaccination, prophylaxis, and treatment are essential in the emergency management. Major issues at all levels of disaster response decision making, including long-range strategic planning, tactical response planning, and real-time operational support are still unresolved and operations research can provide useful techniques for decision management.-JRC.G.2-Global security and crisis managemen

Literature Review - the vaccine supply chain

Vaccination is one of the most effective ways to prevent the outbreak of an infectious disease. This medical intervention also brings about many logistical quest

Impact of vaccine supplies and delays on optimal control of the COVID-19 pandemic: mapping interventions for the Philippines

Background Around the world, controlling the COVID-19 pandemic requires national coordination of multiple intervention strategies. As vaccinations are globally introduced into the repertoire of available interventions, it is important to consider how changes in the local supply of vaccines, including delays in administration, may be addressed through existing policy levers. This study aims to identify the optimal level of interventions for COVID-19 from 2021 to 2022 in the Philippines, which as a developing country is particularly vulnerable to shifting assumptions around vaccine availability. Furthermore, we explore optimal strategies in scenarios featuring delays in vaccine administration, expansions of vaccine supply, and limited combinations of interventions. Methods Embedding our work within the local policy landscape, we apply optimal control theory to the compartmental model of COVID-19 used by the Philippine government’s pandemic surveillance platform and introduce four controls: (a) precautionary measures like community quarantines, (b) detection of asymptomatic cases, (c) detection of symptomatic cases, and (d) vaccinations. The model is fitted to local data using an L-BFGS minimization procedure. Optimality conditions are identified using Pontryagin’s minimum principle and numerically solved using the forward–backward sweep method. Results Simulation results indicate that early and effective implementation of both precautionary measures and symptomatic case detection is vital for averting the most infections at an efficient cost, resulting in \u3e99% role= presentation style= box-sizing: inherit; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3e\u3e99%\u3e99% reduction of infections compared to the no-control scenario. Expanding vaccine administration capacity to 440,000 full immunizations daily will reduce the overall cost of optimal strategy by 25% role= presentation style= box-sizing: inherit; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3e25%25%, while allowing for a faster relaxation of more resource-intensive interventions. Furthermore, delays in vaccine administration require compensatory increases in the remaining policy levers to maintain a minimal number of infections. For example, delaying the vaccines by 180 days (6 months) will result in an 18% role= presentation style= box-sizing: inherit; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3e18%18% increase in the cost of the optimal strategy. Conclusion We conclude with practical insights regarding policy priorities particularly attuned to the Philippine context, but also applicable more broadly in similar resource-constrained settings. We emphasize three key takeaways of (a) sustaining efficient case detection, isolation, and treatment strategies; (b) expanding not only vaccine supply but also the capacity to administer them, and; (c) timeliness and consistency in adopting policy measures

Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia

Disease modelling is one approach for providing new insights into wildlife disease epidemiology. This paper describes a spatio-temporal, stochastic, susceptible- exposed-infected-recovered process model that simulates the potential spread of classical swine fever through a documented, large and free living wild pig population following a simulated incursion. The study area (300 000 km2) was in northern Australia. Published data on wild pig ecology from Australia, and international Classical Swine Fever data was used to parameterise the model. Sensitivity analyses revealed that herd density (best estimate 1-3 pigs km-2), daily herd movement distances (best estimate approximately 1 km), probability of infection transmission between herds (best estimate 0.75) and disease related herd mortality (best estimate 42%) were highly influential on epidemic size but that extraordinary movements of pigs and the yearly home range size of a pig herd were not. CSF generally established (98% of simulations) following a single point introduction. CSF spread at approximately 9 km2 per day with low incidence rates (< 2 herds per day) in an epidemic wave along contiguous habitat for several years, before dying out (when the epidemic arrived at the end of a contiguous sub-population or at a low density wild pig area). The low incidence rate indicates that surveillance for wildlife disease epidemics caused by short lived infections will be most efficient when surveillance is based on detection and investigation of clinical events, although this may not always be practical. Epidemics could be contained and eradicated with culling (aerial shooting) or vaccination when these were adequately implemented. It was apparent that the spatial structure, ecology and behaviour of wild populations must be accounted for during disease management in wildlife. An important finding was that it may only be necessary to cull or vaccinate relatively small proportions of a population to successfully contain and eradicate some wildlife disease epidemics

Quantifying the Effects of Measures to Control Highly Pathogenic Avian Influenza H5N1 in Poultry in Southeast Asia

Despite the ongoing efforts to contain its spread, H5N1 is now considered endemic within poultry in various settings worldwide, threatening both the livelihoods of those involved in poultry production in affected countries and posing a continuous public health risk. The reasons for the varying levels of success in controlling H5N1 in Southeast Asia need to be better understood. In this thesis, various different methods of quantifying the effects of individual control measures, using the types of data available in various different contexts, are discussed and applied. In the first half of this thesis a spatio-temporal survival model is fitted to H5N1 outbreak surveillance data from Vietnam and Thailand using a Bayesian framework in order to account for unobserved infection times. Following vaccination in Vietnam it was found that transmissibility had been successfully reduced but, during a wave of outbreaks in 2007, that this coincided with a reduction in the rate of at which outbreaks were reported following the introduction of infection, limiting the overall impact this reduction in transmissibility had on the total epidemic size. In Thailand, active surveillance was found to be successful in contributing to the control of infection. Furthermore, backyard producers, whilst responsible for the majority of outbreaks, were, on average, less likely to transmit infection than those involved in more intensive production. In the second half of the thesis, the use of final size methods to assess the effectiveness of vaccination from trial data is explored. This involved an investigation into the effects of different assumptions regarding the action by which vaccination confers immunity and fitting estimates of transmissibility to data collected from outbreak investigations in the context of a field trial of vaccination in Indonesia, where, making strong assumptions about the underlying infection process, a reduction in both within and between flock transmissibility was detected for outbreaks occurring in areas where vaccination was being carried out