Commuter Mobility and the Spread of Infectious Diseases: Application to Influenza in France

Commuting data is increasingly used to describe population mobility in epidemic models. However, there is little evidence that the spatial spread of observed epidemics agrees with commuting. Here, using data from 25 epidemics for influenza-like illness in France (ILI) as seen by the Sentinelles network, we show that commuting volume is highly correlated with the spread of ILI. Next, we provide a systematic analysis of the spread of epidemics using commuting data in a mathematical model. We extract typical paths in the initial spread, related to the organization of the commuting network. These findings suggest that an alternative geographic distribution of GP accross France to the current one could be proposed. Finally, we show that change in commuting according to age (school or work commuting) impacts epidemic spread, and should be taken into account in realistic models.     

Adaptive Vaccination Strategies to Mitigate Pandemic Influenza: Mexico as a Case Study

Background

We explore vaccination strategies against pandemic influenza in Mexico using an age-structured transmission model calibrated against local epidemiological data from the Spring 2009 A(H1N1) pandemic.

Methods and Findings

In the context of limited vaccine supplies, we evaluate age-targeted allocation strategies that either prioritize youngest children and persons over 65 years of age, as for seasonal influenza, or adaptively prioritize age groups based on the age patterns of hospitalization and death monitored in real-time during the early stages of the pandemic. Overall the adaptive vaccination strategy outperformed the seasonal influenza vaccination allocation strategy for a wide range of disease and vaccine coverage parameters.

Conclusions

This modeling approach could inform policies for Mexico and other countries with similar demographic features and vaccine resources issues, with regard to the mitigation of the S-OIV pandemic. We also discuss logistical issues associated with the implementation of adaptive vaccination strategies in the context of past and future influenza pandemics.     

Phylodynamic Inference and Model Assessment with Approximate Bayesian Computation: Influenza as a Case Study

A key priority in infectious disease research is to understand the ecological and evolutionary drivers of viral diseases from data on disease incidence as well as viral genetic and antigenic variation. We propose using a simulation-based, Bayesian method known as Approximate Bayesian Computation (ABC) to fit and assess phylodynamic models that simulate pathogen evolution and ecology against summaries of these data. We illustrate the versatility of the method by analyzing two spatial models describing the phylodynamics of interpandemic human influenza virus subtype A(H3N2). The first model captures antigenic drift phenomenologically with continuously waning immunity, and the second epochal evolution model describes the replacement of major, relatively long-lived antigenic clusters. Combining features of long-term surveillance data from the Netherlands with features of influenza A (H3N2) hemagglutinin gene sequences sampled in northern Europe, key phylodynamic parameters can be estimated with ABC. Goodness-of-fit analyses reveal that the irregularity in interannual incidence and H3N2''s ladder-like hemagglutinin phylogeny are quantitatively only reproduced under the epochal evolution model within a spatial context. However, the concomitant incidence dynamics result in a very large reproductive number and are not consistent with empirical estimates of H3N2''s population level attack rate. These results demonstrate that the interactions between the evolutionary and ecological processes impose multiple quantitative constraints on the phylodynamic trajectories of influenza A(H3N2), so that sequence and surveillance data can be used synergistically. ABC, one of several data synthesis approaches, can easily interface a broad class of phylodynamic models with various types of data but requires careful calibration of the summaries and tolerance parameters.     

Rapid Generation of Human-Like Neutralizing Monoclonal Antibodies in Urgent Preparedness for Influenza Pandemics and Virulent Infectious Diseases

Background

The outbreaks of emerging infectious diseases caused by pathogens such as SARS coronavirus, H5N1, H1N1, and recently H7N9 influenza viruses, have been associated with significant mortality and morbidity in humans. Neutralizing antibodies from individuals who have recovered from an infection confer therapeutic protection to others infected with the same pathogen. However, survivors may not always be available for providing plasma or for the cloning of monoclonal antibodies (mAbs).

Methodology/Principal Findings

The genome and the immunoglobulin genes in rhesus macaques and humans are highly homologous; therefore, we investigated whether neutralizing mAbs that are highly homologous to those of humans (human-like) could be generated. Using the H5N1 influenza virus as a model, we first immunized rhesus macaques with recombinant adenoviruses carrying a synthetic gene encoding hemagglutinin (HA). Following screening an antibody phage display library derived from the B cells of immunized monkeys, we cloned selected macaque immunoglobulin heavy chain and light chain variable regions into the human IgG constant region, which generated human-macaque chimeric mAbs exhibiting over 97% homology to human antibodies. Selected mAbs demonstrated potent neutralizing activities against three clades (0, 1, 2) of the H5N1 influenza viruses. The in vivo protection experiments demonstrated that the mAbs effectively protected the mice even when administered up to 3 days after infection with H5N1 influenza virus. In particular, mAb 4E6 demonstrated sub-picomolar binding affinity to HA and superior in vivo protection efficacy without the loss of body weight and obvious lung damage. The analysis of the 4E6 escape mutants demonstrated that the 4E6 antibody bound to a conserved epitope region containing two amino acids on the globular head of HA.

Conclusions/Significance

Our study demonstrated the generation of neutralizing mAbs for potential application in humans in urgent preparedness against outbreaks of new influenza infections or other virulent infectious diseases.     

Emerging and Reemerging Infectious Diseases: Biocomplexity as an Interdisciplinary Paradigm

Understanding factors responsible for reemergence of diseases believed to have been controlled and outbreaks of previously unknown infectious diseases is one of the most difficult scientific problems facing society today. Significant knowledge gaps exist for even the most studied emerging infectious diseases. Coupled with failures in the response to the resurgence of infectious diseases, this lack of information is embedded in a simplistic view of pathogens and disconnected from a social and ecological context, and assumes a linear response of pathogens to environmental change. In fact, the natural reservoirs and transmission rates of most emerging infectious diseases primarily are affected by environmental factors, such as seasonality or meteorological events, typically producing nonlinear responses that are inherently unpredictable. A more realistic view of emerging infectious diseases requires a holistic perspective that incorporates social as well as physical, chemical, and biological dimensions of our planet’s systems. The notion of biocomplexity captures this depth and richness, and most importantly, the interactions of human and natural systems. This article provides a brief review and a synthesis of interdisciplinary approaches and insights employing the biocomplexity paradigm and offers a social–ecological approach for addressing and garnering an improved understanding of emerging infectious diseases. Drawing on findings from studies of cholera and other examples of emerging waterborne, zoonotic, and vectorborne diseases, a “blueprint” for the proposed interdisciplinary research framework is offered which integrates biological processes from the molecular level to that of communities and regional systems, incorporating public health infrastructure and climate aspects.     

感染组学 (infectomics) ———对感染性疾病的总体性和综合性研究

在感染性疾病的范畴内,目前急需一个能有效地、精确地和综合性地研究微生物感染的结构性和功能性基因组学和蛋白质组学 ( 感染组学 ) 的全面方法. 新的方法 ( 如 DNA 和蛋白质微阵列 ) 和传统方法 ( 如分子克隆、 PCR 、基因敲除,加进 (knockin) 和反义术等 ) 的结合将有助于克服今天的困难. 在感染时,微生物及其宿主的全部表型改变 ( 感染组 ) 均由微生物病原体及其宿主的基因组所编码,并在特异的微生物 - 宿主相互作用时的某些环境条件下表达. 微生物及其宿主的全部药物反应 ( 药理组 ) 可用基因组或蛋白质组的方法检出. 分析基因型和表型或表达形式的全基因组方法将最终导致对微生物的发病机理、感染性疾病的快速诊断和控制感染的新策略的全面研究. 感染性疾病中最基本的问题是,如何全面地和综合性地应用感染组学,来了解微生物病原体及其宿主的相互作用.     

A Small Community Model for the Transmission of Infectious Diseases: Comparison of School Closure as an Intervention in Individual-Based Models of an Influenza Pandemic

Background

In the absence of other evidence, modelling has been used extensively to help policy makers plan for a potential future influenza pandemic.

Method

We have constructed an individual based model of a small community in the developed world with detail down to exact household structure obtained from census collection datasets and precise simulation of household demographics, movement within the community and individual contact patterns. We modelled the spread of pandemic influenza in this community and the effect on daily and final attack rates of four social distancing measures: school closure, increased case isolation, workplace non-attendance and community contact reduction. We compared the modelled results of final attack rates in the absence of any interventions and the effect of school closure as a single intervention with other published individual based models of pandemic influenza in the developed world.

Results

We showed that published individual based models estimate similar final attack rates over a range of values for R₀ in a pandemic where no interventions have been implemented; that multiple social distancing measures applied early and continuously can be very effective in interrupting transmission of the pandemic virus for R₀ values up to 2.5; and that different conclusions reached on the simulated benefit of school closure in published models appear to result from differences in assumptions about the timing and duration of school closure and flow-on effects on other social contacts resulting from school closure.

Conclusion

Models of the spread and control of pandemic influenza have the potential to assist policy makers with decisions about which control strategies to adopt. However, attention needs to be given by policy makers to the assumptions underpinning both the models and the control strategies examined.     

Operationalising Factors That Explain the Emergence of Infectious Diseases: A Case Study of the Human Campylobacteriosis Epidemic

A framework of general factors for infectious disease emergence was made operational for Campylobacter utilising explanatory variables including time series and risk factor data. These variables were generated using a combination of empirical epidemiology, case-case and case-control studies, time series analysis, and microbial sub-typing (source attribution, diversity, genetic distance) to unravel the changing/emerging aetiology of human campylobacteriosis. The study focused on Scotland between 1990–2012 where there was a 75% increase in reported cases that included >300% increase in the elderly and 50% decrease in young children. During this period there were three phases 1990–2000 a 75% rise and a 20% fall to 2006, followed by a 19% resurgence. The rise coincided with expansions in the poultry industry, consumption of chicken, and a shift from rural to urban cases. The post-2000 fall occurred across all groups apart from the elderly and coincided with a drop of the prevalence of Campylobacter in chicken and a higher proportion of rural cases. The increase in the elderly was associated with uptake of proton pump inhibitors. During the resurgence the increase was predominantly in adults and the elderly, again there was increasing use of PPIs and high prevalences in chicken and ruminants. Cases associated with foreign travel during the study also increased from 9% to a peak of 16% in 2006 before falling to an estimated 10% in 2011, predominantly in adults and older children. During all three periods source attribution, genetic distance, and diversity measurements placed human isolates most similar to those in chickens. A combination of emergence factors generic for infectious diseases were responsible for the Campylobacter epidemic. It was possible to use these to obtain a putative explanation for the changes in human disease and the potential to make an informed view of how incidence rates may change in the future.     

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.     

Seasonal Influenza Vaccination amongst Medical Students: A Social Network Analysis Based on a Cross-Sectional Study

Introduction

The Chief Medical Officer for England recommends that healthcare workers have a seasonal influenza vaccination in an attempt to protect both patients and NHS staff. Despite this, many healthcare workers do not have a seasonal influenza vaccination. Social network analysis is a well-established research approach that looks at individuals in the context of their social connections. We examine the effects of social networks on influenza vaccination decision and disease dynamics.

Methods

We used a social network analysis approach to look at vaccination distribution within the network of the Lancaster Medical School students and combined these data with the students’ beliefs about vaccination behaviours. We then developed a model which simulated influenza outbreaks to study the effects of preferentially vaccinating individuals within this network.

Results

Of the 253 eligible students, 217 (86%) provided relational data, and 65% of responders had received a seasonal influenza vaccination. Students who were vaccinated were more likely to think other medical students were vaccinated. However, there was no clustering of vaccinated individuals within the medical student social network. The influenza simulation model demonstrated that vaccination of well-connected individuals may have a disproportional effect on disease dynamics.

Conclusions

This medical student population exhibited vaccination coverage levels similar to those seen in other healthcare groups but below recommendations. However, in this population, a lack of vaccination clustering might provide natural protection from influenza outbreaks. An individual student’s perception of the vaccination coverage amongst their peers appears to correlate with their own decision to vaccinate, but the directionality of this relationship is not clear. When looking at the spread of disease within a population it is important to include social structures alongside vaccination data. Social networks influence disease epidemiology and vaccination campaigns designed with information from social networks could be a future target for policy makers.     

Influenza Surveillance and Incidence in a Rural Area in China during the 2009/2010 Influenza Pandemic

Background

Most influenza surveillance is based on data from urban sentinel hospitals; little is known about influenza activity in rural communities. We conducted influenza surveillance in a rural region of China with the aim of detecting influenza activity in the 2009/2010 influenza season.

Methods

The study was conducted from October 2009 to March 2010. Real-time polymerase chain reaction was used to confirm influenza cases. Over-the-counter (OTC) drug sales were daily collected in drugstores and hospitals/clinics. Space-time scan statistics were used to identify clusters of ILI in community. The incidence rate of ILI/influenza was estimated on the basis of the number of ILI/influenza cases detected by the hospitals/clinics.

Results

A total of 434 ILI cases (3.88% of all consultations) were reported; 64.71% of these cases were influenza A (H1N1) pdm09. The estimated incidence rate of ILI and influenza were 5.19/100 and 0.40/100, respectively. The numbers of ILI cases and OTC drug purchases in the previous 7 days were strongly correlated (Spearman rank correlation coefficient [r] = 0.620, P = 0.001). Four ILI outbreaks were detected by space-time permutation analysis.

Conclusions

This rural community surveillance detected influenza A (H1N1) pdm09 activity and outbreaks in the 2009/2010 influenza season and enabled estimation of the incidence rate of influenza. It also provides a scientific data for public health measures.     

Epidemiological Study on Infectious Diarrheal Diseases in Children in a Coastal Rural Area of Kenya

Diarrheal diseases are major causes of morbidity and mortality among children in developing countries. We have analyzed the causative agents of diarrhea in children under five years of age who resided in rural environments but attended a hospital in Malindi, a coastal town in Kenya. Bacterial diarrhea was found in 239 (27.7%) of 862 patients with diarrhea. Diarrheagenic Escherichia coli, including enteropathogenic, enterotoxigenic, and enterohaemorrhagic strains, was isolated from 119 (13.8%) patients, followed by Salmonella spp. (63 cases, 7.3%) and Shigella spp. (56 cases, 6.5%). Intestinal parasites were found in 109 (12.6%) of the patients. Entamoeba histolytica and Giardia lamblia were found in 67 (7.8%) and 42 (4.9%) of the cases, respectively. Rotavirus was found in 69 (16.1%) of 428 cases, a part of the 862 cases. Significant differences in age distribution were seen in diarrheal cases due to Campylobacter spp., G. lamblia, and rotavirus. No significant seasonal incidence of specific pathogens was found, but the number of diarrheal patients was significantly correlated to rainfall. Drinking water was contaminated with bacteria at concentrations ranging from 10³ to 10⁶ CFU/ml in 98% of the households and by coliform bacteria at concentrations of 10² to 10⁵ CFU/ml in 72% of the households. These results suggest that the main routes of infection may be contaminated drinking water and fecal-oral transmission of enteric pathogens. Consequently, we propose that the enhancement of hygienic practice through health education is a feasible control measure of diarrhea in the study area.     

Interactions between Global Health Initiatives and Country Health Systems: The Case of a Neglected Tropical Diseases Control Program in Mali

Background

Recently, a number of Global Health Initiatives (GHI) have been created to address single disease issues in low-income countries, such as poliomyelitis, trachoma, neonatal tetanus, etc.. Empirical evidence on the effects of such GHIs on local health systems remains scarce. This paper explores positive and negative effects of the Integrated Neglected Tropical Disease (NTD) Control Initiative, consisting in mass preventive chemotherapy for five targeted NTDs, on Mali''s health system where it was first implemented in 2007.

Methods and Findings

Campaign processes and interactions with the health system were assessed through participant observation in two rural districts (8 health centres each). Information was complemented by interviews with key informants, website search and literature review. Preliminary results were validated during feedback sessions with Malian authorities from national, regional and district levels. We present positive and negative effects of the NTD campaign on the health system using the WHO framework of analysis based on six interrelated elements: health service delivery, health workforce, health information system, drug procurement system, financing and governance. At point of delivery, campaign-related workload severely interfered with routine care delivery which was cut down or totally interrupted during the campaign, as nurses were absent from their health centre for campaign-related activities. Only 2 of the 16 health centres, characterized by a qualified, stable and motivated workforce, were able to keep routine services running and to use the campaign as an opportunity for quality improvement. Increased workload was compensated by allowances, which significantly improved staff income, but also contributed to divert attention away from core routine activities. While the campaign increased the availability of NTD drugs at country level, parallel systems for drug supply and evaluation requested extra efforts burdening local health systems. The campaign budget barely financed institutional strengthening. Finally, though the initiative rested at least partially on national structures, pressures to absorb donated drugs and reach short-term coverage results contributed to distract energies away from other priorities, including overall health systems strengthening.

Conclusions

Our study indicates that positive synergies between disease specific interventions and nontargeted health services are more likely to occur in robust health services and systems. Disease-specific interventions implemented as parallel activities in fragile health services may further weaken their responsiveness to community needs, especially when several GHIs operate simultaneously. Health system strengthening will not result from the sum of selective global interventions but requires a comprehensive approach.     

Power Analysis for Population-Based Longitudinal Studies Investigating Gene-Environment Interactions in Chronic Diseases: A Simulation Study

Conventional methods for sample size calculation for population-based longitudinal studies tend to overestimate the statistical power by overlooking important determinants of the required sample size, such as the measurement errors and unmeasured etiological determinants, etc. In contrast, a simulation-based sample size calculation, if designed properly, allows these determinants to be taken into account and offers flexibility in accommodating complex study design features. The Canadian Longitudinal Study on Aging (CLSA) is a Canada-wide, 20-year follow-up study of 30,000 people between the ages of 45 and 85 years, with in-depth information collected every 3 years. A simulation study, based on an illness-death model, was conducted to: (1) investigate the statistical power profile of the CLSA to detect the effect of environmental and genetic risk factors, and their interaction on age-related chronic diseases; and (2) explore the design alternatives and implementation strategies for increasing the statistical power of population-based longitudinal studies in general. The results showed that the statistical power to identify the effect of environmental and genetic risk exposures, and their interaction on a disease was boosted when: (1) the prevalence of the risk exposures increased; (2) the disease of interest is relatively common in the population; and (3) risk exposures were measured accurately. In addition, the frequency of data collection every three years in the CLSA led to a slightly lower statistical power compared to the design assuming that participants underwent health monitoring continuously. The CLSA had sufficient power to detect a small (1<hazard ratio (HR)≤1.5) or moderate effect (1.5< HR≤2.0) of the environmental risk exposure, as long as the risk exposure and the disease of interest were not rare. It had enough power to detect a moderate or large (2.0<HR≤3.0) effect of the genetic risk exposure when the prevalence of the risk exposure was not very low (≥0.1) and the disease of interest was not rare (such as diabetes and dementia). The CLSA had enough power to detect a large effect of the gene-environment interaction only when both risk exposures had relatively high prevalence (0.2) and the disease of interest was very common (such as diabetes). The minimum detectable hazard ratios (MDHR) of the CLSA for the environmental and genetic risk exposures obtained from this simulation study were larger than those calculated according to the conventional sample size calculation method. For example, the MDHR for the environmental risk exposure was 1.15 according to the conventional method if the prevalence of the risk exposure was 0.1 and the disease of interest was dementia. In contrast, the MDHR was 1.61 if the same exposure was measured every 3 years with a misclassification rate of 0.1 according to this simulation study. With a given sample size, higher statistical power could be achieved by increasing the measuring frequency in participants with high risk of declining health status or changing risk exposures, and by increasing measurement accuracy of diseases and risk exposures. A properly designed simulation-based sample size calculation is superior to conventional methods when rigorous sample size calculation is necessary.     

The Health Literacy of Hong Kong Chinese Parents with Preschool Children in Seasonal Influenza Prevention: A Multiple Case Study at Household Level

Background

Health literacy influences individual and family health behaviour, health services use, and ultimately health outcomes and health care costs. In Hong Kong, people are at risk of seasonal influenza infection twice a year for three-month periods. Seasonal influenza is significantly associated with an increased number of hospitalized children. There is no research that provides an understanding of parents’ health knowledge and their access to health information concerning seasonal influenza, nor their capacity to effectively manage influenza episodes in household. Such knowledge provides valuable insight into enhancing parents’ health literacy to effectively communicate health messages to their children and support healthy behaviour development through role modelling.

Methods

A multiple case study was employed to gain a multifaceted understanding of parents’ health literacy regarding seasonal influenza prevention. Purposive intensity sampling was adopted to recruit twenty Hong Kong Chinese parents with a healthy three-to-five year old preschool child from three kindergartens. A content analysis was employed to categorize, tabulate and combine data to address the propositions of the study. Comprehensive comparisons were made across cases to reveal the commonalities and differences.

Results

Four major themes were identified: inadequate parents'' knowledge and reported skills and practices related to seasonal influenza prevention; parental knowledge seeking and exchange practices through social connection; parents’ approaches to health information and limited enabling environments including shortage of health resources and uneven resource allocation for health promotion.

Conclusions

The findings recommend that community health professionals can play a critical role in increasing parents’ functional, interactive and critical health literacy; important elements when planning and implementing seasonal influenza health promotion.