Mart L. Stein

Online Respondent-Driven Sampling for Studying Contact Patterns Relevant for the Spread of Close-Contact Pathogens: A Pilot Study in Thailand

Background Information on social interactions is needed to understand the spread of airborne infections through a population. Previous studies mostly collected egocentric information of independent respondents with self-reported information about contacts. Respondent-driven sampling (RDS) is a sampling technique allowing respondents to recruit contacts from their social network. We explored the feasibility of webRDS for studying contact patterns relevant for the spread of respiratory pathogens. Materials and Methods We developed a webRDS system for facilitating and tracking recruitment by Facebook and email. One-day diary surveys were conducted by applying webRDS among a convenience sample of Thai students. Students were asked to record numbers of contacts at different settings and self-reported influenza-like-illness symptoms, and to recruit four contacts whom they had met in the previous week. Contacts were asked to do the same to create a network tree of socially connected individuals. Correlations between linked individuals were analysed to investigate assortativity within networks. Results We reached up to 6 waves of contacts of initial respondents, using only non-material incentives. Forty-four (23.0%) of the initially approached students recruited one or more contacts. In total 257 persons participated, of which 168 (65.4%) were recruited by others. Facebook was the most popular recruitment option (45.1%). Strong assortative mixing was seen by age, gender and education, indicating a tendency of respondents to connect to contacts with similar characteristics. Random mixing was seen by reported number of daily contacts. Conclusions Despite methodological challenges (e.g. clustering among respondents and their contacts), applying RDS provides new insights in mixing patterns relevant for close-contact infections in real-world networks. Such information increases our knowledge of the transmission of respiratory infections within populations and can be used to improve existing modelling approaches. It is worthwhile to further develop and explore webRDS for the detection of clusters of respiratory symptoms in social networks.

Health System Resource Gaps and Associated Mortality from Pandemic Influenza across Six Asian Territories

Background Southeast Asia has been the focus of considerable investment in pandemic influenza preparedness. Given the wide variation in socio-economic conditions, health system capacity across the region is likely to impact to varying degrees on pandemic mitigation operations. We aimed to estimate and compare the resource gaps, and potential mortalities associated with those gaps, for responding to pandemic influenza within and between six territories in Asia. Methods and Findings We collected health system resource data from Cambodia, Indonesia (Jakarta and Bali), Lao PDR, Taiwan, Thailand and Vietnam. We applied a mathematical transmission model to simulate a “mild-to-moderate” pandemic influenza scenario to estimate resource needs, gaps, and attributable mortalities at province level within each territory. The results show that wide variations exist in resource capacities between and within the six territories, with substantial mortalities predicted as a result of resource gaps (referred to here as “avoidable” mortalities), particularly in poorer areas. Severe nationwide shortages of mechanical ventilators were estimated to be a major cause of avoidable mortalities in all territories except Taiwan. Other resources (oseltamivir, hospital beds and human resources) are inequitably distributed within countries. Estimates of resource gaps and avoidable mortalities were highly sensitive to model parameters defining the transmissibility and clinical severity of the pandemic scenario. However, geographic patterns observed within and across territories remained similar for the range of parameter values explored. Conclusions The findings have important implications for where (both geographically and in terms of which resource types) investment is most needed, and the potential impact of resource mobilization for mitigating the disease burden of an influenza pandemic. Effective mobilization of resources across administrative boundaries could go some way towards minimizing avoidable deaths.

Health service resource needs for pandemic influenza in developing countries: a linked transmission dynamics, interventions and resource demand model

We used a mathematical model to describe a regional outbreak and extrapolate the underlying health-service resource needs. This model was designed to (i) estimate resource gaps and quantities of resources needed, (ii) show the effect of resource gaps, and (iii) highlight which particular resources should be improved. We ran the model, parameterized with data from the 2009 H1N1v pandemic, for two provinces in Thailand. The predicted number of preventable deaths due to resource shortcomings and the actual resource needs are presented for two provinces and for Thailand as a whole. The model highlights the potentially huge impact of health-system resource availability and of resource gaps on health outcomes during a pandemic and provides a means to indicate where efforts should be concentrated to effectively improve pandemic response programmes.

Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator

BackgroundHealth care planning for pandemic influenza is a challenging task which requires predictive models by which the impact of different response strategies can be evaluated. However, current preparedness plans and simulations exercises, as well as freely available simulation models previously made for policy makers, do not explicitly address the availability of health care resources or determine the impact of shortages on public health. Nevertheless, the feasibility of health systems to implement response measures or interventions described in plans and trained in exercises depends on the available resource capacity. As part of the AsiaFluCap project, we developed a comprehensive and flexible resource modelling tool to support public health officials in understanding and preparing for surges in resource demand during future pandemics.ResultsThe AsiaFluCap Simulator is a combination of a resource model containing 28 health care resources and an epidemiological model. The tool was built in MS Excel© and contains a user-friendly interface which allows users to select mild or severe pandemic scenarios, change resource parameters and run simulations for one or multiple regions. Besides epidemiological estimations, the simulator provides indications on resource gaps or surpluses, and the impact of shortages on public health for each selected region. It allows for a comparative analysis of the effects of resource availability and consequences of different strategies of resource use, which can provide guidance on resource prioritising and/or mobilisation. Simulation results are displayed in various tables and graphs, and can also be easily exported to GIS software to create maps for geographical analysis of the distribution of resources.ConclusionsThe AsiaFluCap Simulator is freely available software (http://www.cdprg.org) which can be used by policy makers, policy advisors, donors and other stakeholders involved in preparedness for providing evidence based and illustrative information on health care resource capacities during future pandemics. The tool can inform both preparedness plans and simulation exercises and can help increase the general understanding of dynamics in resource capacities during a pandemic. The combination of a mathematical model with multiple resources and the linkage to GIS for creating maps makes the tool unique compared to other available software.

Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and The Netherlands using respondent-driven sampling

Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in the Netherlands and Thailand using a similar online respondent-driven method. By asking participants to recruit contact persons we studied network links relevant for the transmission of respiratory infections. We studied correlations between recruiter and recruited contacts to investigate mixing patterns in the observed social network components. In both countries, mixing patterns were assortative by demographic variables and random by total numbers of contacts. However, in Thailand participants reported overall more contacts which resulted in higher effective contact rates. Our findings provide new insights on numbers of contacts and mixing patterns in two different populations. These data could be used to improve parameterisation of mathematical models used to design control strategies. Although the spread of infections through populations depends on more factors, found similarities suggest that spread may be similar in the Netherlands and Thailand.

Choosing pandemic parameters for pandemic preparedness planning: A comparison of pandemic scenarios prior to and following the influenza A(H1N1) 2009 pandemic

BACKGROUND Mathematical models are used to explore various possible scenarios with regard to an influenza pandemic. We studied the ranges of parameter values in modelling studies on preparedness prior to 2009 in relation to the estimated parameter values of the influenza A(H1N1) 2009 pandemic. METHODS AND FINDINGS We conducted two systematic literature searches, one aimed at epidemic parameter values that were used in pre-2009 pandemic influenza models, and the other aimed at estimates of epidemic variables from data collected during the influenza A(H1N1) 2009 pandemic. The range of parameter values used to inform models was broad and covered the range of estimates of these parameters inferred from the influenza A(H1N1) 2009 pandemic. CONCLUSION The current practice of selecting a range of plausible parameter values for influenza works well for modelling scenarios where effects of different interventions are explored to guide public health decision makers. To narrow down this range of plausible parameter values to the actual value during a pandemic, using incoming data, real-time estimation might provide an additional benefit.

Hepatitis B in Moroccan-Dutch: a qualitative study into determinants of screening participation.

Abstract Background Chronic hepatitis B (HBV) leads to an increased risk for liver cirrhosis and liver cancer. In the Netherlands, chronic HBV prevalence in the general population is 0.20%, but 3.77% in first generation immigrants. Our aim was to identify determinants associated with the intention to participate in HBV testing among first generation Moroccan immigrants, one of the two largest immigrant groups targeted for screening. Methods Semi-structured interviews were held with first (n = 9) and second generation (n = 10) Moroccan-Dutch immigrants, since second generation immigrants frequently act as their parents’ brokers in healthcare. Results Most participants had little knowledge about hepatitis B, but had a positive attitude towards screening. Facilitators for screening intention were perceived susceptibility to and severity of disease, positive attitude regarding prevention, wishing to know their hepatitis B status and to prevent potential hepatitis B transmission to others. Additional cultural facilitators included fear (of developing cancer), and existing high health care utilization; a religious facilitator was the responsibility for one’s own health and that of others. Barriers included lack of awareness and knowledge, practical issues, not having symptoms, negative attitude regarding prevention, fear about the test result and low-risk perception. A cultural barrier was shame and stigma, and a religious barrier was fatalism. Conclusion We identified important facilitators and barriers, which we found, can be interpreted differently. Specific and accurate information should be provided, accompanied by strategies to address shame and stigma, in which Islamic religious leaders could play a role in bringing information across.

Hepatitis B in Moroccan-Dutch: a quantitative study into determinants of screening participation

BackgroundIn November 2016, the Dutch Health Council recommended hepatitis B (HBV) screening for first-generation immigrants from HBV endemic countries. However, these communities show relatively low attendance rates for screening programmes, and our knowledge on their participation behaviour is limited. We identified determinants associated with the intention to request an HBV screening test in first-generation Moroccan-Dutch immigrants. We also investigated the influence of non-refundable costs for HBV screening on their intention.MethodsOffline and online questionnaires were distributed among first- and second/third-generation Moroccan-Dutch immigrants using respondent-driven sampling. Random forest analyses were conducted to determine which determinants had the greatest impact on (1) the intention to request an HBV screening test on one’s own initiative, and (2) the intention to participate in non-refundable HBV screening at €70,-.ResultsOf the 379 Moroccan-Dutch respondents, 49.3% intended to request a test on their own initiative, and 44.1% were willing to attend non-refundable screening for €70,-. Clarity regarding infection status, not having symptoms, fatalism, perceived self-efficacy, and perceived risk of having HBV were the strongest predictors to request a test. Shame and stigma, fatalism, perceived burden of screening participation, and social influence of Islamic religious leaders had the greatest predictive value for not intending to participate in screening at €70,- non-refundable costs. Perceived severity and possible health benefit were facilitators for this intention measure. These predictions were satisfyingly accurate, as the random forest method retrieved area under the curve scores of 0.72 for intention to request a test and 0.67 for intention to participate in screening at €70,- non-refundable costs.ConclusionsBy the use of respondent-driven sampling, we succeeded in studying screening behaviour among a hard-to-reach minority population. Despite the limitations associated with correlated data and the sampling method, we recommend to (1) incorporate clarity regarding HBV status, (2) stress the risk of an asymptomatic infection, (3) emphasise mother-to-child transmission as the main transmission route, and (4) team up with Islamic religious leaders to help decrease elements of fatalism, shame, and stigma to enhance screening uptake of Moroccan immigrants in the Netherlands.

A comparison between a deterministic, compartmental model and an individual based-stochastic model for simulating the transmission dynamics of pandemic influenza

Simulation models are often used in the research area of epidemiology to understand characteristics of disease outbreaks. As a result, they are used by authorities to better design intervention methods and to better plan the allocation of medical resources. Previous work make use of many different types of simulation models with an agent-based model, e.g., Taiwan simulation system, and an equation-based model, e.g., AsiaFluCap simulation system, being the two most popular ones. Some comparison studies has been attempted in the past to understand the limits, efficiency, and usability of some model. However, there was little studies to justify why one model is used instead of the other. In this paper, instead of studying the two most popular models one by one, we try to do a comparative study between these two most popular ones. By observing that one model can outperform the other in some cases, and vice versa, we hence study conditions that which one should be used. Furthermore, previous studies show little results in the issue of allocating medical resources. Our paper studies and compares the two models using medical resources allocation as one of our primary concerns. As a conclusion, we come out with a general guideline to help model designers to pick one that fits the given needs better.