The objective of Web-based expert epidemic intelligence systems is to detect health threats. The Global Health Security Initiative (GHSI) Early Alerting and Reporting (EAR) project was launched to assess the feasibility and opportunity for pooling epidemic intelligence data from seven expert systems. EAR participants completed a qualitative survey to document epidemic intelligence strategies and to assess perceptions regarding the systems performance. Timeliness and sensitivity were rated highly illustrating the value of the systems for epidemic intelligence. Weaknesses identified included representativeness, completeness and flexibility. These findings were corroborated by the quantitative analysis performed on signals potentially related to influenza A/H5N1 events occurring in March 2010. For the six systems for which this information was available, the detection rate ranged from 31% to 38%, and increased to 72% when considering the virtual combined system. The effective positive predictive values ranged from 3% to 24% and F1-scores ranged from 6% to 27%. System sensitivity ranged from 38% to 72%. An average difference of 23% was observed between the sensitivities calculated for human cases and epizootics, underlining the difficulties in developing an efficient algorithm for a single pathology. However, the sensitivity increased to 93% when the virtual combined system was considered, clearly illustrating complementarities between individual systems. The average delay between the detection of A/H5N1 events by the systems and their official reporting by WHO or OIE was 10.2 days (95% CI: 6.7–13.8). This work illustrates the diversity in implemented epidemic intelligence activities, differences in system's designs, and the potential added values and opportunities for synergy between systems, between users and between systems and users.

Background

Victoria was the first state in Australia to experience community transmission of influenza A(H1N1)pdm09. We undertook a descriptive epidemiological analysis of the first 1,000 notified cases to describe the epidemic associated with school children and explore implications for school closure and antiviral distribution policy in revised pandemic plans.

Methods

Records of the first 1,000 laboratory-confirmed cases of influenza A(H1N1)pdm09 notified to the Victorian Government Department of Health between 20 May and 5 June 2009 were extracted from the state’s notifiable infectious diseases database. Descriptive analyses were conducted on case demographics, symptoms, case treatment, prophylaxis of contacts and distribution of cases in schools.

Results

Two-thirds of the first 1,000 cases were school-aged (5–17 years) with cases in 203 schools, particularly along the north and western peripheries of the metropolitan area. Cases in one school accounted for nearly 8% of all cases but the school was not closed until nine days after symptom onset of the first identified case. Amongst all cases, cough (85%) was the most commonly reported symptom followed by fever (68%) although this was significantly higher in primary school children (76%). The risk of hospitalisation was 2%. The median time between illness onset and notification of laboratory confirmation was four days, with only 10% of cases notified within two days of onset and thus eligible for oseltamivir treatment. Nearly 6,000 contacts were followed up for prophylaxis.

Conclusions

With a generally mild clinical course and widespread transmission before its detection, limited and short-term school closures appeared to have minimal impact on influenza A(H1N1)pdm09 transmission. Antiviral treatment could rarely be delivered to cases within 48 hours of symptom onset. These scenarios and lessons learned from them need to be incorporated into revisions of pandemic plans.

The total number of influenza cases with medical attendance has been estimated from sentinel surveillance data in Japan under a random sampling assumption of sentinel medical institutions among the total medical institutions. The 2009 pandemic offered a research opportunity to validate the sentinel-based estimation method using the estimated proportion of infections measured by the population-wide seroepidemiological survey employing hemagglutinin inhibition (HI) assay. For the entire population, we estimated the age-standardized proportion of infections at 28.5% and 23.5% using cut-off values of HI titer at 1 : 20 and 1 : 40, respectively. Investigating the age profiles, we show that the estimated influenza-like illness (ILI) cases with medical attendance exceeded the estimated infections among those aged from 0 to 19 years, indicating an overestimation of the magnitude by sentinel-based estimation method. The ratio of estimated cases to estimated infections decreased as a function of age. Examining the geographic distributions, no positive correlation was identified between the estimated cases and infections. Our findings indicate a serious technical limitation of the so-called multiplier method in appropriately quantifying the risk of influenza due to limited specificity of ILI and reporting bias. A seroepidemiological study should be planned in advance of a pandemic.

Use of the final size distribution of minor outbreaks for the estimation of the reproduction numbers of supercritical epidemic processes has yet to be considered. We used a branching process model to derive the final size distribution of minor outbreaks, assuming a reproduction number above unity, and applying the method to final size data for pneumonic plague. Pneumonic plague is a rare disease with only one documented major epidemic in a spatially limited setting. Because the final size distribution of a minor outbreak needs to be normalized by the probability of extinction, we assume that the dispersion parameter (k) of the negative-binomial offspring distribution is known, and examine the sensitivity of the reproduction number to variation in dispersion. Assuming a geometric offspring distribution with k = 1, the reproduction number was estimated at 1.16 (95% confidence interval: 0.97–1.38). When less dispersed with k = 2, the maximum likelihood estimate of the reproduction number was 1.14. These estimates agreed with those published from transmission network analysis, indicating that the human-to-human transmission potential of the pneumonic plague is not very high. Given only minor outbreaks, transmission potential is not sufficiently assessed by directly counting the number of offspring. Since the absence of a major epidemic does not guarantee a subcritical process, the proposed method allows us to conservatively regard epidemic data from minor outbreaks as supercritical, and yield estimates of threshold values above unity.

Background

Animal transmission studies can provide important insights into host, viral and environmental factors affecting transmission of viruses including influenza A. The basic unit of analysis in typical animal transmission experiments is the presence or absence of transmission from an infectious animal to a susceptible animal. In studies comparing two groups (e.g. two host genetic variants, two virus strains, or two arrangements of animal cages), differences between groups are evaluated by comparing the proportion of pairs with successful transmission in each group. The present study aimed to discuss the significance and power to estimate transmissibility and identify differences in the transmissibility based on one-to-one trials. The analyses are illustrated on transmission studies of influenza A viruses in the ferret model.

Methodology/Principal Findings

Employing the stochastic general epidemic model, the basic reproduction number, R0, is derived from the final state of an epidemic and is related to the probability of successful transmission during each one-to-one trial. In studies to estimate transmissibility, we show that 3 pairs of infectious/susceptible animals cannot demonstrate a significantly higher transmissibility than R0 = 1, even if infection occurs in all three pairs. In comparisons between two groups, at least 4 pairs of infectious/susceptible animals are required in each group to ensure high power to identify significant differences in transmissibility between the groups.

Conclusions

These results inform the appropriate sample sizes for animal transmission experiments, while relating the observed proportion of infected pairs to R0, an interpretable epidemiological measure of transmissibility. In addition to the hypothesis testing results, the wide confidence intervals of R0 with small sample sizes also imply that the objective demonstration of difference or similarity should rest on firmly calculated sample size.

Background

Prisoners are at high risk of developing tuberculosis (TB), causing morbidity and mortality. Prison facilities encounter many challenges in TB screening procedures and TB control. This review explores screening practices for detection of TB and describes limitations of TB control in prison facilities worldwide.

Methods

A systematic search of online databases (e.g., PubMed and Embase) and conference abstracts was carried out. Research papers describing screening and diagnostic practices among prisoners were included. A total of 52 articles met the inclusion criteria. A meta-analysis of TB prevalence in prison facilities by screening and diagnostic tools was performed.

Results

The most common screening tool was symptom questionnaires (63·5%), mostly reporting presence of cough. Microscopy of sputum with Ziehl-Neelsen staining and solid culture were the most frequently combined diagnostic methods (21·2%). Chest X-ray and tuberculin skin tests were used by 73·1% and 50%, respectively, as either a screening and/or diagnostic tool. Median TB prevalence among prisoners of all included studies was 1,913 cases of TB per 100,000 prisoners (interquartile range [IQR]: 332–3,517). The overall annual median TB incidence was 7·0 cases per 1000 person-years (IQR: 2·7–30·0). Major limitations for successful TB control were inaccuracy of diagnostic algorithms and the lack of adequate laboratory facilities reported by 61·5% of studies. The most frequent recommendation for improving TB control and case detection was to increase screening frequency (73·1%).

Discussion

TB screening algorithms differ by income area and should be adapted to local contexts. In order to control TB, prison facilities must improve laboratory capacity and frequent use of effective screening and diagnostic tools. Sustainable political will and funding are critical to achieve this.

Many infections can be transmitted between animals and humans. The epidemiological roles of different species can vary from important reservoirs to dead-end hosts. Here, we present a method to identify transmission cycles in different combinations of species from field data. We used this method to synthesise epidemiological and ecological data from Bipindi, Cameroon, a historical focus of gambiense Human African Trypanosomiasis (HAT, sleeping sickness), a disease that has often been considered to be maintained mainly by humans. We estimated the basic reproduction number of gambiense HAT in Bipindi and evaluated the potential for transmission in the absence of human cases. We found that under the assumption of random mixing between vectors and hosts, gambiense HAT could not be maintained in this focus without the contribution of animals. This result remains robust under extensive sensitivity analysis. When using the distributions of species among habitats to estimate the amount of mixing between those species, we found indications for an independent transmission cycle in wild animals. Stochastic simulation of the system confirmed that unless vectors moved between species very rarely, reintroduction would usually occur shortly after elimination of the infection from human populations. This suggests that elimination strategies may have to be reconsidered as targeting human cases alone would be insufficient for control, and reintroduction from animal reservoirs would remain a threat. Our approach is broadly applicable and could reveal animal reservoirs critical to the control of other infectious diseases.

Author Summary

Gambiense sleeping sickness is a disease transmitted by tsetse flies that mostly affects rural populations in sub-Saharan Africa. Although the parasite that causes the disease can be found in many different wild and domestic animal species, the disease has often been claimed to be maintained mostly by humans. Currently, fewer than 10,000 human cases are reported per year across Africa, and it has been suggested that elimination of gambiense sleeping sickness is feasible. We analysed human and animal case data from a well-known endemic focus of sleeping sickness in Cameroon, to quantify the contribution of the different species to the circulation of the parasite. In a wide range of scenarios, we found that animals are crucial for maintenance in the disease. When informing our model by the distribution of species among habitats as measured in the field, we found indications for independent transmission cycles in animals. This suggests that a risk of reintroduction from animal into human populations would remain even if the disease were eliminated from those human populations.

Background

During the very early stage of the 2009 pandemic, mass chemoprophylaxis was implemented as part of containment measure. The purposes of the present study were to systematically review the retrospective studies that investigated the effectiveness of antiviral prophylaxis during the 2009 pandemic, and to explicitly estimate the effectiveness by employing a mathematical model.

Methods

A systematic review identified 17 articles that clearly defined the cases and identified exposed individuals based on contact tracing. Analysing a specific school-driven outbreak, we estimated the effectiveness of antiviral prophylaxis using a renewal equation model. Other parameters, including the reproduction number and the effectiveness of antiviral treatment and school closure, were jointly estimated.

Results

Based on the systematic review, median secondary infection risks (SIRs) among exposed individuals with and without prophylaxis were estimated at 2.1% (quartile: 0, 12.2) and 16.6% (quartile: 8.4, 32.4), respectively. A very high heterogeneity in the SIR was identified with an estimated I2 statistic at 71.8%. From the outbreak data in Madagascar, the effectiveness of mass chemoprophylaxis in reducing secondary transmissions was estimated to range from 92.8% to 95.4% according to different model assumptions and likelihood functions, not varying substantially as compared to other parameters.

Conclusions

Only based on the meta-analysis of retrospective studies with different study designs and exposure settings, it was not feasible to estimate the effectiveness of antiviral prophylaxis in reducing transmission. However, modelling analysis of a single outbreak successfully yielded an estimate of the effectiveness that appeared to be robust to model assumptions. Future studies should fill the data gap that has existed in observational studies and allow mathematical models to be used for the analysis of meta-data.

Epidemiological determinants of successful vaccine development were explored using measurable biological variables including antigenic stability and requirement of T-cell immunity. Employing a logistic regression model, we demonstrate that a high affinity with blood and immune cells and pathogen interactions (e.g. interference) would be the risk factors of failure for vaccine development.

The transcriptional nuclear factor binding to the Y box of human leukocyte antigen genes (NF-Y) for the C5a receptor (C5aR) gene is active in erythroblasts. However, the roles of the C5aR in erythropoiesis are unclear. We have previously demonstrated that apoptotic cell-derived ribosomal protein S19 (RP S19) oligomers exhibit extraribosomal functions in promoting monocyte chemotaxis and proapoptosis via the C5aR without receptor internalisation. In contrast to the extraribosomal functions of the RP S19, a proapoptotic signal in pro-EBs, which is caused by mutations in the RP S19 gene, is associated with the inherited erythroblastopenia, Diamond-Blackfan anaemia. In this study, we detected C5aR expression and RP S19 oligomer generation in human erythroleukemia K562 cells during haemin-induced erythropoiesis. Under monocell culture conditions, the differentiation into K562 erythrocyte-like cells was enhanced following the overexpression of Wild-type RP S19. Conversely, the differentiation was repressed following the overexpression of mutant RP S19. An RP S19 oligomer inhibitor and a C5aR inhibitor blocked the association of the K562 basophilic EB-like cells and the THP-1 macrophage-like cells under coculture conditions. When bound to RP S19 oligomers, the C5aR may exhibit dual functions as a connector for the EB-macrophage island and as a sensor for EB differentiation in the bone marrow.

The immunity to pandemic influenza A(H1N1)pdm09 in Sweden before and after the outbreaks in 2009 and 2010 was investigated in a seroepidemiological study. Serum samples were collected at four time points: during 2007 (n = 1968), in October 2009 (n = 2218), in May 2010 (n = 2638) and in May 2011 (n = 2513) and were tested for hemagglutination inhibition (HI) antibodies. In 2007, 4.9% of the population had pre-existing HI titres ≥40, with the highest prevalence (20.0%) in 15–24 year-olds, followed by ≥80 year-olds (9.3%). The overall prevalence of HI titres ≥40 had not changed significantly in October 2009. In May 2010 the prevalence had increased to 48.6% with the highest percentages in 5–14 year-olds (76.2%) andlowest in 75–79 year-olds (18.3%). One year later the prevalence of HI titres ≥40 had increased further to 52.2%. Children 5–14 years had the highest incidence of infection and vaccine uptake as well as the highest post-pandemic protective antibody levels. In contrast, the elderly had high vaccine uptake and low attack rate but low levels of protective antibodies, underlining that factors other than HI antibodies are involved in protection against influenza A(H1N1)pdm09. However, for all age-groups the seroprevalence was stable or increasing between 2010 and 2011, indicating that both vaccine- and infection-induced antibodies were long-lived.

We discuss models for rapidly disseminating infectious diseases during mass gatherings (MGs), using influenza as a case study. Recent innovations in modeling and forecasting influenza transmission dynamics at local, regional, and global scales have made influenza a particularly attractive model scenario for MG. We discuss the behavioral, medical, and population factors for modeling MG disease transmission, review existing model formulations, and highlight key data and modeling gaps related to modeling MG disease transmission. We argue that the proposed improvements will help integrate infectious-disease models in MG health contingency plans in the near future, echoing modeling efforts that have helped shape influenza pandemic preparedness plans in recent years.

Background

Many novel vaccines can cover only a fraction of all antigenic types of a pathogen. Vaccine effectiveness (VE) in the presence of interactions between vaccine strains and others is complicated by the interacting transmission dynamics among all strains. The present study investigated how the VE estimates measured in the field, based on estimated odds ratio or relative risks, are scaled by vaccination coverage and the transmission dynamics in the presence of cross-protective immunity between two strains, i.e. vaccine and non-vaccine strains.

Methodology/Principal Findings

Two different types of epidemiological models, i.e. with and without re-infection by the same antigenic type, were investigated. We computed the relative risk of infection and the odds ratio of vaccination, the latter of which has been measured by indirect cohort method as applied to vaccine effectiveness study of Streptococcus pneumoniae. The VE based on the relative risk was less sensitive to epidemiological dynamics such as cross-protective immunity and vaccination coverage than the VE calculated from the odds ratio, and this was especially the case for the model without re-infection. Vaccine-induced (cross-protective) immunity against a non-vaccine strain appeared to yield the highest impact on the VE estimate calculated from the odds ratio of vaccination.

Conclusion

It is essential to understand the transmission dynamics of non-vaccine strains so that epidemiological methods can appropriately measure both the direct and indirect population impact of vaccination. For pathogens with interacting antigenic types, the most valid estimates of VE, that are unlikely to be biased by the transmission dynamics, may be obtained from longitudinal prospective studies that permit estimation of the VE based on the relative risk of infection among vaccinated compared to unvaccinated individuals.

Background

The number of outbreaks of highly pathogenic avian influenza virus of the H5N1 subtype (HPAIV H5N1) over the past 5 years has been drastically reduced in China but sporadic infections in poultry and humans are still occurring. In this study, we aimed to investigate seasonal patterns in the association between the movement of live poultry originating from southern China and HPAIV H5N1 infection history in humans and poultry in China.

Methodology/Principal Findings

During January to April 2010, longitudinal questionnaire surveys were carried out monthly in four wholesale live bird markets (LBMs) in Hunan and Guangxi provinces of South China. Using social network analysis, we found an increase in the number of observed links and degree centrality between LBMs and poultry sources in February and March compared to the months of January and April. The association of some live poultry traders (LPT’s) with a limited set of counties (within the catchment area of LBMs) in the months of February and March may support HPAIV H5N1 transmission and contribute to perpetuating HPAIV H5N1 virus circulation among certain groups of counties. The connectivity among counties experiencing human infection was significantly higher compared to counties without human infection for the months of January, March and April. Conversely, counties with poultry infections were found to be significantly less connected than counties without poultry infection for the month of February.

Conclusions/Significance

Our results show that temporal variation in live poultry trade in Southern China around the Chinese New Year festivities is associated with higher HPAIV H5N1 infection risk in humans and poultry. This study has shown that capturing the dynamic nature of poultry trade networks in Southern China improves our ability to explain the spatiotemporal dissemination in avian influenza viruses in China.

Background

Climate change is affecting many physical and biological processes worldwide. Anticipating its effects at the level of populations and species is imperative, especially for organisms of conservation or management concern. Previous studies have focused on estimating future species distributions and extinction probabilities directly from current climatic conditions within their geographical ranges. However, relationships between climate and population parameters may be so complex that to make these high-level predictions we need first to understand the underlying biological processes driving population size, as well as their individual response to climatic alterations. Therefore, the objective of this study is to investigate the influence that climate change may have on species population dynamics through altering breeding season.

Methodology/Principal Findings

We used a mechanistic model based on drivers of rabbit reproductive physiology together with demographic simulations to show how future climate-driven changes in breeding season result in contrasting rabbit population trends across Europe. In the Iberian Peninsula, where rabbits are a native species of high ecological and economic value, breeding seasons will shorten and become more variable leading to population declines, higher extinction risk, and lower resilience to perturbations. Whereas towards north-eastern countries, rabbit numbers are expected to increase through longer and more stable reproductive periods, which augment the probability of new rabbit invasions in those areas.

Conclusions/Significance

Our study reveals the type of mechanisms through which climate will cause alterations at the species level and emphasizes the need to focus on them in order to better foresee large-scale complex population trends. This is especially important in species like the European rabbit whose future responses may aggravate even further its dual keystone/pest problematic. Moreover, this approach allows us to predict not only distribution shifts but also future population status and growth, and to identify the demographic parameters on which to focus to mitigate global change effects.

Dengue is a vector-borne disease recognized as the major arbovirose with four immunologically distant dengue serotypes coexisting in many endemic areas. Several mathematical models have been developed to understand the transmission dynamics of dengue, including the role of cross-reactive antibodies for the four different dengue serotypes. We aimed to review deterministic models of dengue transmission, in order to summarize the evolution of insights for, and provided by, such models, and to identify important characteristics for future model development. We identified relevant publications using PubMed and ISI Web of Knowledge, focusing on mathematical deterministic models of dengue transmission. Model assumptions were systematically extracted from each reviewed model structure, and were linked with their underlying epidemiological concepts. After defining common terms in vector-borne disease modelling, we generally categorised fourty-two published models of interest into single serotype and multiserotype models. The multi-serotype models assumed either vector-host or direct host-to-host transmission (ignoring the vector component). For each approach, we discussed the underlying structural and parameter assumptions, threshold behaviour and the projected impact of interventions. In view of the expected availability of dengue vaccines, modelling approaches will increasingly focus on the effectiveness and cost-effectiveness of vaccination options. For this purpose, the level of representation of the vector and host populations seems pivotal. Since vector-host transmission models would be required for projections of combined vaccination and vector control interventions, we advocate their use as most relevant to advice health policy in the future. The limited understanding of the factors which influence dengue transmission as well as limited data availability remain important concerns when applying dengue models to real-world decision problems.

Background

The household secondary attack proportion is commonly used to measure the transmissibility of an infectious disease.

Methods

We analyzed the final outbreak distributions of pandemic A(H1N1), seasonal A(H1N1) and A(H3N2) infections identified in paired sera collected from members of 117 Hong Kong households in April and August-October 2009.

Results

The estimated community probability of infection overall was higher for children than adults; the probability was similar for pandemic A(H1N1) and seasonal A(H3N2) influenza. The household secondary attack proportion for pandemic A(H1N1) was higher in children than adults, whereas for seasonal A(H3N2) it was similar in children and adults. The estimated secondary attack proportions were similar for seasonal A(H3N2) and pandemic A(H1N1) after excluding persons with higher baseline antibody titers from analysis.

Conclusions

Pandemic and seasonal influenza A viruses had similar age-specific transmissibility in a cohort of initially uninfected households after adjustment for baseline immunity.

Providing valid and reliable estimates of the transmissibility and severity of pandemic influenza in real time is key to guide public health policymaking. In particular, early estimates of the transmissibility are indispensable for determining the type and intensity of interventions. A recent study by House and colleagues in BMC Medicine devised a stochastic transmission model to estimate the unbiased risk of transmission within households, applying the method to datasets of the 2009 A/H1N1 influenza pandemic. Here, we discuss future challenges in household transmission studies and underscore the need to systematically collect epidemiological data to decipher the household transmission dynamics. We emphasize the need to consider three critical issues for future improvements: (i) capturing age-dependent heterogeneity within households calls for intensive modeling efforts, (ii) the timeline of observation during the course of an epidemic and the length of follow-up should be aligned with study objectives, and (iii) the use of laboratory methods, especially molecular techniques, is encouraged to distinguish household transmissions from those arising in the community.

See related article: http://www.biomedcentral.com/1741-7015/10/117

We derive a new method to estimate the age specific incidence of an infection with a differential mortality, using individual level infection status data from successive surveys. The method consists of a) an SI-type model to express the incidence rate in terms of the prevalence and its derivatives as well as the difference in mortality rate, and b) a maximum likelihood approach to estimate the prevalence and its derivatives. Estimates can in principle be obtained for any chosen age and time, and no particular assumptions are made about the epidemiological or demographic context. This is in contrast with earlier methods for estimating incidence from prevalence data, which work with aggregated data, and the aggregated effect of demographic and epidemiological rates over the time interval between prevalence surveys. Numerical simulation of HIV epidemics, under the presumption of known excess mortality due to infection, shows improved control of bias and variance, compared to previous methods. Our analysis motivates for a) effort to be applied to obtain accurate estimates of excess mortality rates as a function of age and time among HIV infected individuals and b) use of individual level rather than aggregated data in order to estimate HIV incidence rates at times between two prevalence surveys.

Background

Pastoralists in low-income countries usually live in close proximity to their animals and thus represent an important repository of information about livestock disease. Since wild and domestic animals often mix freely whilst grazing, pastoralists are also able to observe first-hand the diseases that are present in wildlife and as such are key informants in disease outbreaks in sylvatic animals. We report here the findings of the first study of the knowledge and role of Masai pastoralists in mange in wildlife and livestock in Masai Mara, Kenya.

Methodology/Principal Findings

In this paper we describe the knowledge of mange accrued by 56 Masai pastoralists in Kenya and how they respond to it in both wildlife and livestock. In total, 52 (93%) pastoralists had a clear idea of the clinical appearance of mange, 13 (23%) understood its aetiology and 37 (66%) knew that mites were the causal agent. Thirty-nine (69%) believed that mange cross-infection between domestic and wild animals occurs, while 48 (85%) had observed mange in domestic animals including sheep (77%), goats (57%), dogs (24%) and cattle (14%). The pastoralists had also observed wild animals infected with mange, above all lions (19%), gazelles (14%), cheetahs (12%) and wildebeests (2%). In 68% of cases Masai pastoralists treat mange infection or apply control measures, most commonly via the topical use of acaricides (29%) and/or the reporting of the outbreak to the veterinary authorities (21%). In the period 2007–2011, Kenya Wildlife Service received 24 warnings of 59 wild animals with mange-like lesions from the Masai Mara pastoralist community. The reported species were cheetah, lion, wild dog, Thomson’s gazelle and wildebeest.

Conclusion

Masai pastoralists have good knowledge of mange epidemiology and treatment. Their observations and the treatments they apply are valuable in the control of this disease in both wild and domestic animals.

The epidemiological mechanisms behind the W-shaped age-specific influenza mortality during the Spanish influenza (H1N1) pandemic 1918-19 have yet to be fully clarified. The present study aimed to develop a formal hypothesis: tuberculosis (TB) was associated with the W-shaped influenza mortality from 1918-19. Three pieces of epidemiological information were assessed: (i) the epidemic records containing the age-specific numbers of cases and deaths of influenza from 1918-19, (ii) an outbreak record of influenza in a Swiss TB sanatorium during the pandemic, and (iii) the age-dependent TB mortality over time in the early 20th century. Analyzing the data (i), we found that the W-shaped pattern was not only seen in mortality but also in the age-specific case fatality ratio, suggesting the presence of underlying age-specific risk factor(s) of influenza death among young adults. From the data (ii), TB was shown to be associated with influenza death (P = 0.09), and there was no influenza death among non-TB controls. The data (iii) were analyzed by employing the age-period-cohort model, revealing harvesting effect in the period function of TB mortality shortly after the 1918-19 pandemic. These findings suggest that it is worthwhile to further explore the role of TB in characterizing the age-specific risk of influenza death.

Background

High coverage of personal protection measures that kill mosquitoes dramatically reduce malaria transmission where vector populations depend upon human blood. However, most primary malaria vectors outside of sub-Saharan Africa can be classified as “very zoophagic,” meaning they feed occasionally (<10% of blood meals) upon humans, so personal protection interventions have negligible impact upon their survival.

Methods and Findings

We extended a published malaria transmission model to examine the relationship between transmission, control, and the baseline proportion of bloodmeals obtained from humans (human blood index). The lower limit of the human blood index enables derivation of simplified models for zoophagic vectors that (1) Rely on only three field-measurable parameters. (2) Predict immediate and delayed (with and without assuming reduced human infectivity, respectively) impacts of personal protection measures upon transmission. (3) Illustrate how appreciable indirect communal-level protection for non-users can be accrued through direct personal protection of users. (4) Suggest the coverage and efficacy thresholds required to attain epidemiological impact. The findings suggest that immediate, indirect, community-wide protection of users and non-users alike may linearly relate to the efficacy of a user’s direct personal protection, regardless of whether that is achieved by killing or repelling mosquitoes. High protective coverage and efficacy (≥80%) are important to achieve epidemiologically meaningful impact. Non-users are indirectly protected because the two most common species of human malaria are strict anthroponoses. Therefore, the small proportion of mosquitoes that are killed or diverted while attacking humans can represent a large proportion of those actually transmitting malaria.

Conclusions

Simplified models of malaria transmission by very zoophagic vectors may be used by control practitioners to predict intervention impact interventions using three field-measurable parameters; the proportion of human exposure to mosquitoes occurring when an intervention can be practically used, its protective efficacy when used, and the proportion of people using it.

Estimating the case fatality ratio (CFR) of a novel strain of influenza virus during the early stage of the pandemic is one of key epidemiological tasks to be conducted as rapid research response. Past experience during the epidemics of severe acute respiratory syndrome (SARS) and influenza A (H1N1-2009) posed several technical challenges in estimating the CFR in real time. The present study aimed to develop a simple method to estimate the CFR based on readily available datasets, that is, confirmed cases and deaths, while addressing some of the known technical issues. To assess the reliability and validity of the proposed method, we examined the minimum length of time required for the assigned CFR to be included within the 95% confidence intervals and for the estimated CFR to be below a prespecified cut-off value by means of Monte Carlo simulations. Overall, the smaller the transmission potential was, the longer it took to compare the estimated CFR against the cut-off value. If policymaking and public health response have to be made based on the CFR estimate derived from the proposed method and readily available data, it should be noted that the successful estimation may take longer than a few months.

In recent years, the early detection of low pathogenicity avian influenza (LPAI) viruses in poultry has become increasingly important, given their potential to mutate into highly pathogenic viruses. However, evaluations of LPAI surveillance have mainly focused on prevalence and not on the ability to act as an early warning system. We used a simulation model based on data from Italian LPAI epidemics in turkeys to evaluate different surveillance strategies in terms of their performance as early warning systems. The strategies differed in terms of sample size, sampling frequency, diagnostic tests, and whether or not active surveillance (i.e., routine laboratory testing of farms) was performed, and were also tested under different epidemiological scenarios. We compared surveillance strategies by simulating within-farm outbreaks. The output measures were the proportion of infected farms that are detected and the farm reproduction number (Rh). The first one provides an indication of the sensitivity of the surveillance system to detect within-farm infections, whereas Rh reflects the effectiveness of outbreak detection (i.e., if detection occurs soon enough to bring an epidemic under control). Increasing the sampling frequency was the most effective means of improving the timeliness of detection (i.e., it occurs earlier), whereas increasing the sample size increased the likelihood of detection. Surveillance was only effective in preventing an epidemic if actions were taken within two days of sampling. The strategies were not affected by the quality of the diagnostic test, although performing both serological and virological assays increased the sensitivity of active surveillance. Early detection of LPAI outbreaks in turkeys can be achieved by increasing the sampling frequency for active surveillance, though very frequent sampling may not be sustainable in the long term. We suggest that, when no LPAI virus is circulating yet and there is a low risk of virus introduction, a less frequent sampling approach might be admitted, provided that the surveillance is intensified as soon as the first outbreak is detected.