28 April 2015

Research Committee Articles of the week for April 27, 2015

Articles from Apr_27_2015

Research Committee Selected Articles for the Week of Apr_27_2015

The role of residence times in two-patch dengue transmission dynamics and optimal strategies

The reemergence and geographical dispersal of vector-borne diseases challenge global health experts around the world and in particular, dengue poses increasing difficulties in the Americas, due in part to explosive urban and semi-urban growth, increases of within and between region mobility, the absence of a vaccine, and the limited resources available for public health services. In this work, a simple deterministic two-patch model is introduced to assess the impact of dengue transmission dynamics in heterogeneous environments. The two-patch system models the movement (e.g. urban versus rural areas residence times) of individuals between and within patches/environments using residence-time matrices with entries that budget within and between host patch relative residence times, under the assumption that only the human budgets their residence time across regions. Three scenarios are considered: (i) resident hosts in Patch i visit patch j, where i?. j but not the other way around, a scenario referred to as unidirectional motion; (ii) symmetric bi-directional motion; and (iii) asymmetric bi-directional motion. Optimal control theory is used to identify and evaluate patch-specific control measures aimed at reducing dengue prevalence in humans and vectors at a minimal cost. Optimal policies are computed under different residence-matrix configurations mentioned above as well as transmissibility scenarios characterized by the magnitude of the basic reproduction number. Optimal patch-specific polices can ameliorate the impact of epidemic outbreaks substantially when the basic reproduction number is moderate. The final patch-specific epidemic size variation increases as the residence time matrix moves away from the symmetric case (asymmetry). As expected, the patch where individuals spend most of their time or in the patch where transmissibility is higher tend to support larger patch-specific final epidemic sizes. Hence, focusing on intervention that target areas where indiv

Incorporation of spatial interactions in location networks to identify critical geo-referenced routes for assessing disease control measures on a large-scale campus

Respiratory diseases mainly spread through interpersonal contact. Class suspension is the most direct strategy to prevent the spread of disease through elementary or secondary schools by blocking the contact network. However, as university students usually attend courses in different buildings, the daily contact patterns on a university campus are complicated, and once disease clusters have occurred, suspending classes is far from an efficient strategy to control disease spread. The purpose of this study is to propose a methodological framework for generating campus location networks from a routine administration database, analyzing the community structure of the network, and identifying the critical links and nodes for blocking respiratory disease transmission. The data comes from the student enrollment records of a major comprehensive university in Taiwan. We combined the social network analysis and spatial interaction model to establish a geo-referenced community structure among the classroom buildings. We also identified the critical links among the communities that were acting as contact bridges and explored the changes in the location network after the sequential removal of the high-risk buildings. Instead of conducting a questionnaire survey, the study established a standard procedure for constructing a location network on a large-scale campus from a routine curriculum database. We also present how a location network structure at a campus could function to target the high-risk buildings as the bridges connecting communities for blocking disease transmission. © 2015, by the authors.

Spatial, temporal, and spatiotemporal analysis of malaria in Hubei Province, China from 2004-2011

Background: Malaria remains a public health concern in Hubei Province despite the significant decrease in malaria incidence over the past decades. Furthermore, history reveals that malaria transmission is unstable and prone to local outbreaks in Hubei Province. Thus, understanding spatial, temporal, and spatiotemporal distribution of malaria is needed for the effective control and elimination of this disease in Hubei Province. Methods: Annual malaria incidence at the county level was calculated using the malaria cases reported from 2004 to 2011 in Hubei Province. Geographical information system (GIS) and spatial scan statistic method were used to identify spatial clusters of malaria cases at the county level. Pure retrospective temporal analysis scanning was performed to detect the temporal clusters of malaria cases with high rates using the discrete Poisson model. The space-time cluster was detected with high rates through the retrospective space-time analysis scanning using the discrete Poisson model. Results: The overall malaria incidence decreased to a low level from 2004 to 2011. The purely spatial cluster of malaria cases from 2004 to 2011 showed that the disease was not randomly distributed in the study area. A total of 11 high-risk counties were determined through Local Moran's I analysis from 2004 to 2011. The method of spatial scan statistics identified different 11 significant spatial clusters between 2004 and 2011. The space-time clustering analysis determined that the most likely cluster included 13 counties, and the time frame was from April 2004 to November 2007. Conclusions: The GIS application and scan statistical technique can provide means to detect spatial, temporal, and spatiotemporal distribution of malaria, as well as to identify malaria high-risk areas. This study could be helpful in prioritizing resource assignment in high-risk areas for future malaria control and elimination. © 2015 Xia et al.; licensee BioMed Central.

Reflections on New York City’s 1947 Smallpox Vaccination Program and Its 1976 Swine Influenza Immunization Program

In 1947, a smallpox outbreak occurred in New York City with a total of twelve cases and two deaths. In order to contain this outbreak, the New York City Department of Health launched a mass immunization campaign that over a period of some 60 days vaccinated 6.35 million people. This article examines in detail the epidemiology of this outbreak and the measures employed to contain it. In 1976, a swine influenza strain was isolated among a few recruits at a US Army training camp at Fort Dix, New Jersey. It was concluded at the time that this virus possibly represented a re-appearance of the 1918 influenza pandemic influenza strain. As a result, a mass national immunization program was launched by the federal government. From its inception, the program encountered a myriad of challenges ranging from doubts that it was even necessary to the development of Guillain-Barré paralysis among some vaccine recipients. This paper examines the planning for and implementation of the swine flu immunization program in New York City. It also compares it to the smallpox vaccination program of 1947. Despite equivalent financial and personnel resources, leadership and organizational skills, the 1976 program only immunized approximately a tenth of the number of New York City residents vaccinated in 1947. The reasons for these marked differences in outcomes are discussed in detail. © 2015 Springer Science+Business Media New York

A rational approach to estimating the surgical demand elasticity needed to guide manpower reallocation during contagious outbreaks

Background Emerging infectious diseases continue to pose serious threats to global public health. So far, however, few published study has addressed the need for manpower reallocation needed in hospitals when such a serious contagious outbreak occurs. Aim To quantify the demand elasticity of the major surgery types in order to guide future manpower reallocation during contagious outbreaks. Materials and Methods Based on a nationwide research database in Taiwan, we extracted the monthly volumes of major surgery types for the period 1998-2003, which covered the SARS period, in order to carry out a time series analysis. The demand elasticity of each surgery type was then estimated by autoregressive integrated moving average (ARIMA) analysis. Results During the study period, the surgical volumes of most selected surgery types either increased or remained steady. We categorized these surgery types into low-, moderate- And high-elastic groups according to their demand elasticity. Appendectomy, 'open reduction of fracture with internal fixation' and 'free skin graft' were in the low demand elasticity group. Transurethral prostatectomy and extracorporeal shockwave lithotripsy (ESWL) were in the high demand elasticity group. The manpower of the departments carrying out the surgeries with low demand elasticity should be maintained during outbreaks. In contrast, departments in charge of surgeries mainly with high demand elasticity, like urology departments, may be in a position to have part of their staff reallocated. Conclusions Taking advantage of the demand variation during the SARS period in 2003, we adopted the concept of demand elasticity and used a time series approach to figure out an effective index of demand elasticity for various types of surgery that could be used as a rational reference to carry out manpower reallocation during contagious outbreak situations. © 2015 Tsao et al.

Selection of key recommendations for quality indicators describing good quality outbreak response

Background: The performance of recommended control measures is necessary for quick and uniform infectious disease outbreak control. To assess whether these procedures are performed, a valid set of quality indicators (QIs) is required. The goal of this study was to select a set of key recommendations that can be systematically translated into QIs to measure the quality of infectious disease outbreak response from the perspective of disaster emergency responders and infectious disease control professionals. Methods: Applying the Rand modified Delphi procedure, the following steps were taken to systematically select a set of key recommendations: extraction of recommendations from relevant literature; appraisal of the recommendations in terms of relevance through questionnaires to experts; expert meeting to discuss recommendations; prioritization of recommendations through a second questionnaire; and final expert meeting to approve the selected set. Infectious disease physicians and nurses, policymakers and communication experts participated in the expert group (n = 48). Results: In total, 54 national and international publications were systematically searched for recommendations, yielding over 200 recommendations. The Rand modified Delphi procedure resulted in a set of 65 key recommendations. The key recommendations were categorized into 10 domains describing the whole response pathway from outbreak recognition to aftercare. Conclusion: This study provides a set of key recommendations that represents 'good quality of response to an infectious disease outbreak'. These key recommendations can be systematically translated into QIs. Organizations and professionals involved in outbreak control can use these QIs to monitor the quality of response to infectious disease outbreaks and to assess in which domains improvement is needed. © Belfroid et al.; licensee BioMed Central.

A large multi-pathogen gastroenteritis outbreak caused by drinking contaminated water from antique neighbourhood fountains, Erzurum city, Turkey, December 2012

We investigated a gastroenteritis outbreak in Erzurum city, Turkey in December 2012 to identify its cause and mode of transmission. We defined a probable case as onset of diarrhoea (?3 episodes/day) or vomiting, plus fever or nausea or abdominal pain during 19-27 December, 2012 in an Erzurum city resident. In a case-control study we compared exposures of 95 randomly selected probable cases and 95 neighbourhood-matched controls. We conducted bacterial culture and real-time multiplex PCR for identification of pathogens. During the week before illness onset, 72% of cases and 15% of controls only drank water from antique neighbourhood fountains; conversely, 16% of cases and 65% of controls only drank bottled or tap water (adjusted odds ratio 20, 95% confidence interval 4·6-84, after controlling for age and sex using conditional logistic regression). Of eight stool specimens collected, two were positive for Shigella sonnei, one for astrovirus, one for astrovirus and norovirus, and one for astrovirus and rotavirus. Water samples from the fountains had elevated total coliform (38-300/100 ml) and Escherichia coli (22-198/100 ml) counts. In conclusion, drinking contaminated fountain water caused this multi-pathogen outbreak. Residents should stop drinking water from these fountains, and clean water from the water treatment plant should be connected to the fountains.

Infectious disease transmission and contact networks in wildlife and livestock

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Public health incident management: Logistical and operational aspects of the 2009 initial outbreak of H1N1 influenza in Mexico

Hosting an international outbreak response team can pose a challenge to jurisdictions not familiar with incident management frameworks. Basic principles of team forming, organizing, and executing mission critical activities require simple and flexible communication that can be easily understood by the host country's public health leadership and international support agencies. Familiarity with incident command system principles before a public health emergency could save time and effort during the initial phases of the response and aid in operationalizing and sustaining complex field activities throughout the response. The 2009 initial outbreak of H1N1 in Mexico highlighted the importance of adequately organizing and managing limited resources and expertise using incident management principles. This case study describes logistical and operational aspects of the response and highlights challenges faced during this response that may be relevant to the organization of public health responses and incidents requiring international assistance and cooperation.

Infectious disease and group size: More than just a numbers game

Increased risk of infectious disease is assumed to be a major cost of group living, yet empirical evidence for this effect is mixed. We studied whether larger social groups are more subdivided structurally. If so, the social subdivisions that form in larger groups may act as barriers to the spread of infection, weakening the association between group size and infectious disease. To investigate this ‘social bottleneck’ hypothesis, we examined the association between group size and four network structure metrics in 43 vertebrate and invertebrate species. We focused on metrics involving modularity, clustering, distance and centralization. In a meta-analysis of intraspecific variation in social networks, modularity showed positive associations with network size, with a weaker but still positive effect in cross-species analyses. Network distance also showed a positive association with group size when using intraspecific variation. We then used a theoretical model to explore the effects of subgrouping relative to other effects that influence disease spread in socially structured populations. Outbreaks reached higher prevalence when groups were larger, but subgrouping reduced prevalence. Subgrouping also acted as a ‘brake’ on disease spread between groups.We suggest research directions to understand the conditions under which larger groups become more subdivided, and to devise new metrics that account for subgrouping when investigating the links between sociality and infectious disease risk. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Early warning system for dengue outbreak – a preliminary approach using time series forecasting

Dengue is one of the challenges faced by tropical countries such as India. The impacts of climate changes can affect dengue outbreak. From the previous studies it is examined that there is an association between metrological variables and dengue incidence using Time series analyses. The proposed study is to explore a systematic approach that provides an early warning system for dengue outbreak of a given region.. The time series data is decomposed and estimated the trend, seasonal and irregular compounds. Time series analysis using ARIMA and SARIMA model along with temperature variants is found to be effective for dengue predication. The prediction is based on the benchmark data of Dengue incidence and metrological data using R-tool version 3.0.2. Experimental result shows that the metrological variables (Maximum temperature, Humidity and Rainfall) significantly influence the dengue incidence for the given dataset. Error values of the SARIMA model provides comparatively lower with respect to ARIMA. © Research India Publications.

Statistical estimations for Plasmodium vivax malaria in South Korea

Objective: To calculate the numbers of weekly infections and prevalence of malaria, and to predict future trend of malaria incidences in South Korea. Methods: Weekly incidences of malaria for 13 years from the period 2001-2013 in South Korea were analyzed. The back-calculation equations were used with incubation period distributions. The maximum likelihood estimation for Poisson model was also used. The confidence intervals of the estimates were obtained by a bootstrap method. A regression model for time series of malaria incidences over 13 years was fitted by the non-linear least squares method, and used to predict futuretrend. Results: The estimated infection curve is narrower and more concentrated in the summer than in the incidence distribution. Infection started around the 19th week and was over around the 41st week. The maximum weekly infection 110 was obtained at the 29th week. The prevalence at the first week was around 496 persons, the minimum number was 366 at 22nd week, and the maximum prevalence was 648 at 34th week. Prevalence drops in late spring with people that falling ill and had had long incubation periods and rose in the summer with new infections. Our future forecast based on the regression model was that an increase at year 2014 compared to 2013 may reach a peak (at maximum about 70 weekly cases) at year 2015, with a decreasing trend after then. Conclusions: This work shows that back-calculation methods could work well in estimating the infection rates and the prevalence of malaria. The obtained results can be useful in establishing an efficient preventive program for malaria infection. The method presented here can be used in other countries where incidence data and incubation period are available. © 2015 Hainan Medical College.

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