School of Mathematics and Statistics - Research Publications
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ItemTurnover of Village Chickens Undermines Vaccine Coverage to Control HPAI H5N1(WILEY, 2017-02)Highly pathogenic avian influenza (HPAI) subtype H5N1 remains an enzootic disease of village chickens in Indonesia, posing ongoing risk at the animal-human interface. Previous modelling showed that the fast natural turnover of chicken populations might undermine herd immunity after vaccination, although actual details of how this effect applies to Indonesia's village chicken population have not been determined. We explored the turnover effect in Indonesia's scavenging and mixed populations of village chickens using an extended Leslie matrix model parameterized with data collected from village chicken flocks in Java region, Indonesia. Population dynamics were simulated for 208 weeks; the turnover effect was simulated for 16 weeks after vaccination in two 'best case' scenarios, where the whole population (scenario 1), or birds aged over 14 days (scenario 2), were vaccinated. We found that the scavenging and mixed populations have different productive traits. When steady-state dynamics are reached, both populations are dominated by females (54.5%), and 'growers' and 'chicks' represent the most abundant age stages with 39% and 38% in the scavenging, and 60% and 25% in the mixed population, respectively. Simulations showed that the population turnover might reduce the herd immunity below the critical threshold that prevents the re-emergence of HPAI H5N1 4-8 weeks (scavenging) and 6-9 weeks (mixed population) after vaccination in scenario 1, and 2-6 weeks (scavenging) and 4-7 weeks (mixed population) after vaccination in scenario 2. In conclusion, we found that Indonesia's village chicken population does not have a unique underlying population dynamic and therefore, different turnover effects on herd immunity may be expected after vaccination; nonetheless, our simulations carried out in best case scenarios highlight the limitations of current vaccine technologies to control HPAI H5N1. This suggests that the improvements and complementary strategies are necessary and must be explored.
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ItemNo Preview AvailablePandemic controllability: a concept to guide a proportionate and flexible operational response to future influenza pandemics(OXFORD UNIV PRESS, 2014-03)The 2009 H1N1 influenza pandemic posed challenges for governments worldwide. Strategies designed to limit community transmission, such as antiviral deployment, were largely ineffective due to both feasibility constraints and the generally mild nature of disease, resulting in incomplete case ascertainment. Reviews of national pandemic plans have identified pandemic impact, primarily linked to measures of transmissibility and severity, as a key concept to incorporate into the next generation of plans. While an assessment of impact provides the rationale under which interventions may be warranted, it does not directly provide an assessment on whether particular interventions may be effective. Such considerations motivate our introduction of the concept of pandemic controllability. For case-targeted interventions, such as antiviral treatment and post-exposure prophylaxis, we identify the visibility and transmissibility of a pandemic as the key drivers of controllability. Taking a case-study approach, we suggest that high-impact pandemics, for which control is most desirable, are likely uncontrollable with case-targeted interventions. Strategies that do not rely on the identification of cases may prove relatively more effective. By introducing a pragmatic framework for relating the assessment of impact to the ability to mitigate an epidemic (controllability), we hope to address a present omission identified in pandemic response plans.
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ItemHousehold transmission of respiratory viruses - assessment of viral, individual and household characteristics in a population study of healthy Australian adults(BMC, 2012-12-11)BACKGROUND: Household transmission of influenza-like illness (ILI) may vary with viral and demographic characteristics. We examined the effect of these factors in a population-based sample of adults with ILI. METHODS: We conducted a prospective cohort study in community-dwelling Australian adults nested within an influenza vaccine effectiveness trial. On presentation with ILI, participants were swabbed for a range of respiratory viruses and asked to return a questionnaire collecting details of household members with or without similar symptoms. We used logistic and Poisson regression to assess the key characteristics of household transmission. RESULTS: 258 participants from multi-occupancy households experienced 279 ILI episodes and returned a questionnaire. Of these, 183 were the primary case in the household allowing assessment of factors associated with transmission. Transmission was significantly associated in univariate analyses with female sex (27% vs. 13%, risk ratio (RR) = 2.13 (1.08, 4.21)) and the presence of a child in the house (33% vs. 17%, RR = 1.90 (1.11, 3.26)). The secondary household attack proportion (SHAP) was 0.14, higher if influenza was isolated (RR = 2.1 (1.0, 4.5)). Vaccinated participants who nonetheless became infected with influenza had a higher SHAP (Incidence RR = 5.24 (2.17, 12.6)). CONCLUSIONS: The increased SHAP in households of vaccinated participants who nonetheless had confirmed influenza infection supports the hypothesis that in years of vaccine mismatch, not only is influenza vaccine less protective for the vaccine recipient, but that the population's immunity is also lower.
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ItemLikely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia(WORLD HEALTH ORGANIZATION, 2012-04)OBJECTIVE: To assess the likely benefit of the interventions under consideration for use in Mongolia during future influenza pandemics. METHODS: A stochastic, compartmental patch model of susceptibility, exposure, infection and recovery was constructed to capture the key effects of several interventions--travel restrictions, school closure, generalized social distancing, quarantining of close contacts, treatment of cases with antivirals and prophylaxis of contacts--on the dynamics of influenza epidemics. The likely benefit and optimal timing and duration of each of these interventions were assessed using Latin-hypercube sampling techniques, averaging across many possible transmission and social mixing parameters. FINDINGS: Timely interventions could substantially alter the time-course and reduce the severity of pandemic influenza in Mongolia. In a moderate pandemic scenario, early social distancing measures decreased the mean attack rate from around 10% to 7-8%. Similarly, in a severe pandemic scenario such measures cut the mean attack rate from approximately 23% to 21%. In both moderate and severe pandemic scenarios, a suite of non-pharmaceutical interventions proved as effective as the targeted use of antivirals. Targeted antiviral campaigns generally appeared more effective in severe pandemic scenarios than in moderate pandemic scenarios. CONCLUSION: A mathematical model of pandemic influenza transmission in Mongolia indicated that, to be successful, interventions to prevent transmission must be triggered when the first cases are detected in border regions. If social distancing measures are introduced at this stage and implemented over several weeks, they may have a notable mitigating impact. In low-income regions such as Mongolia, social distancing may be more effective than the large-scale use of antivirals.
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ItemReducing disease burden in an influenza pandemic by targeted delivery of neuraminidase inhibitors: mathematical models in the Australian context(BMC, 2016-10-10)BACKGROUND: Many nations maintain stockpiles of neuraminidase inhibitor (NAI) antiviral agents for use in influenza pandemics to reduce transmission and mitigate the course of clinical infection. Pandemic preparedness plans include the use of these stockpiles to deliver proportionate responses, informed by emerging evidence of clinical impact. Recent uncertainty about the effectiveness of NAIs has prompted these nations to reconsider the role of NAIs in pandemic response, with implications for pandemic planning and for NAI stockpile size. METHODS: We combined a dynamic model of influenza epidemiology with a model of the clinical care pathways in the Australian health care system to identify effective NAI strategies for reducing morbidity and mortality in pandemic events, and the stockpile requirements for these strategies. The models were informed by a 2015 assessment of NAI effectiveness against susceptibility, pathogenicity, and transmission of influenza. RESULTS: Liberal distribution of NAIs for early treatment in outpatient settings yielded the greatest benefits in all of the considered scenarios. Restriction of community-based treatment to risk groups was effective in those groups, but failed to prevent the large proportion of cases arising from lower risk individuals who comprise the majority of the population. CONCLUSIONS: These targeted strategies are only effective if they can be deployed within the constraints of existing health care infrastructure. This finding highlights the critical importance of identifying optimal models of care delivery for effective emergency health care response.
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ItemNo Preview AvailableEpidemic forecasts as a tool for public health: interpretation and (re)calibration(WILEY, 2018-02)OBJECTIVE: Recent studies have used Bayesian methods to predict timing of influenza epidemics many weeks in advance, but there is no documented evaluation of how such forecasts might support the day-to-day operations of public health staff. METHODS: During the 2015 influenza season in Melbourne, Australia, weekly forecasts were presented at Health Department surveillance unit meetings, where they were evaluated and updated in light of expert opinion to improve their accuracy and usefulness. RESULTS: Predictive capacity of the model was substantially limited by delays in reporting and processing arising from an unprecedented number of notifications, disproportionate to seasonal intensity. Adjustment of the predictive algorithm to account for these delays and increased reporting propensity improved both current situational awareness and forecasting accuracy. CONCLUSIONS: Collaborative engagement with public health practitioners in model development improved understanding of the context and limitations of emerging surveillance data. Incorporation of these insights in a quantitative model resulted in more robust estimates of disease activity for public health use. Implications for public health: In addition to predicting future disease trends, forecasting methods can quantify the impact of delays in data availability and variable reporting practice on the accuracy of current epidemic assessment. Such evidence supports investment in systems capacity.
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ItemIndigenous Australian household structure: a simple data collection tool and implications for close contact transmission of communicable diseases(PEERJ INC, 2017-10-26)Households are an important location for the transmission of communicable diseases. Social contact between household members is typically more frequent, of greater intensity, and is more likely to involve people of different age groups than contact occurring in the general community. Understanding household structure in different populations is therefore fundamental to explaining patterns of disease transmission in these populations. Indigenous populations in Australia tend to live in larger households than non-Indigenous populations, but limited data are available on the structure of these households, and how they differ between remote and urban communities. We have developed a novel approach to the collection of household structure data, suitable for use in a variety of contexts, which provides a detailed view of age, gender, and room occupancy patterns in remote and urban Australian Indigenous households. Here we report analysis of data collected using this tool, which quantifies the extent of crowding in Indigenous households, particularly in remote areas. We use these data to generate matrices of age-specific contact rates, as used by mathematical models of infectious disease transmission. To demonstrate the impact of household structure, we use a mathematical model to simulate an influenza-like illness in different populations. Our simulations suggest that outbreaks in remote populations are likely to spread more rapidly and to a greater extent than outbreaks in non-Indigenous populations.
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ItemNo Preview AvailableCharacterising pandemic severity and transmissibility from data collected during first few hundred studies(ELSEVIER SCIENCE BV, 2017-06)Early estimation of the probable impact of a pandemic influenza outbreak can assist public health authorities to ensure that response measures are proportionate to the scale of the threat. Recently, frameworks based on transmissibility and severity have been proposed for initial characterization of pandemic impact. Data requirements to inform this assessment may be provided by "First Few Hundred" (FF100) studies, which involve surveillance-possibly in person, or via telephone-of household members of confirmed cases. This process of enhanced case finding enables detection of cases across the full spectrum of clinical severity, including the date of symptom onset. Such surveillance is continued until data for a few hundred cases, or satisfactory characterization of the pandemic strain, has been achieved. We present a method for analysing these data, at the household level, to provide a posterior distribution for the parameters of a model that can be interpreted in terms of severity and transmissibility of a pandemic strain. We account for imperfect case detection, where individuals are only observed with some probability that can increase after a first case is detected. Furthermore, we test this methodology using simulated data generated by an independent model, developed for a different purpose and incorporating more complex disease and social dynamics. Our method recovers transmissibility and severity parameters to a high degree of accuracy and provides a computationally efficient approach to estimating the impact of an outbreak in its early stages.
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ItemInfluence of Contact Definitions in Assessment of the Relative Importance of Social Settings in Disease Transmission Risk(PUBLIC LIBRARY SCIENCE, 2012-02-16)BACKGROUND: Realistic models of disease transmission incorporating complex population heterogeneities require input from quantitative population mixing studies. We use contact diaries to assess the relative importance of social settings in respiratory pathogen spread using three measures of person contact hours (PCH) as proxies for transmission risk with an aim to inform bipartite network models of respiratory pathogen transmission. METHODS AND FINDINGS: Our survey examines the contact behaviour for a convenience sample of 65 adults, with each encounter classified as occurring in a work, retail, home, social, travel or "other" setting. The diary design allows for extraction of PCH-interaction (cumulative time in face-face conversational or touch interaction with contacts)--analogous to the contact measure used in several existing surveys--as well as PCH-setting (product of time spent in setting and number of people present) and PCH-reach (product of time spent in setting and number of people in close proximity). Heterogeneities in day-dependent distribution of risk across settings are analysed using partitioning and cluster analyses and compared between days and contact measures. Although home is typically the highest-risk setting when PCH measures isolate two-way interactions, its relative importance compared to social and work settings may reduce when adopting a more inclusive contact measure that considers the number and duration of potential exposure events. CONCLUSIONS: Heterogeneities in location-dependent contact behaviour as measured by contact diary studies depend on the adopted contact definition. We find that contact measures isolating face-face conversational or touch interactions suggest that contact in the home dominates, whereas more inclusive contact measures indicate that home and work settings may be of higher importance. In the absence of definitive knowledge of the contact required to facilitate transmission of various respiratory pathogens, it is important for surveys to consider alternative contact measures.
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ItemOn the Role of CD8+ T Cells in Determining Recovery Time from Influenza Virus Infection(FRONTIERS MEDIA SA, 2016-12-20)Myriad experiments have identified an important role for CD8+ T cell response mechanisms in determining recovery from influenza A virus infection. Animal models of influenza infection further implicate multiple elements of the immune response in defining the dynamical characteristics of viral infection. To date, influenza virus models, while capturing particular aspects of the natural infection history, have been unable to reproduce the full gamut of observed viral kinetic behavior in a single coherent framework. Here, we introduce a mathematical model of influenza viral dynamics incorporating innate, humoral, and cellular immune components and explore its properties with a particular emphasis on the role of cellular immunity. Calibrated against a range of murine data, our model is capable of recapitulating observed viral kinetics from a multitude of experiments. Importantly, the model predicts a robust exponential relationship between the level of effector CD8+ T cells and recovery time, whereby recovery time rapidly decreases to a fixed minimum recovery time with an increasing level of effector CD8+ T cells. We find support for this relationship in recent clinical data from influenza A (H7N9) hospitalized patients. The exponential relationship implies that people with a lower level of naive CD8+ T cells may receive significantly more benefit from induction of additional effector CD8+ T cells arising from immunological memory, itself established through either previous viral infection or T cell-based vaccines.