Decision makers are responsible for directing staffing, logistics, selecting public health interventions, communicating to professionals and the public, planning future response needs, and ...establishing strategic and tactical priorities along with their funding requirements. Decision makers need to rapidly synthesize data from different experts across multiple disciplines, bridge data gaps and translate epidemiological analysis into an operational set of decisions for disease control. Analytic approaches can be defined for specific response phases: investigation, scale-up and control. These approaches include: improved applications of quantitative methods to generate insightful epidemiological descriptions of outbreaks; robust investigations of causal agents and risk factors; tools to assess response needs; identifying and monitoring optimal interventions or combinations of interventions; and forecasting for response planning. Data science and quantitative approaches can improve decision-making in outbreak response. To realize these benefits, we need to develop a structured approach that will improve the quality and timeliness of data collected during outbreaks, establish analytic teams within the response structure and define a research agenda for data analytics in outbreak response. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
Severe illness due to 2009 pandemic A(H1N1) infection has been reported among persons who are obese or morbidly obese. We assessed whether obesity is a risk factor for hospitalization and death due ...to 2009 pandemic influenza A(H1N1), independent of chronic medical conditions considered by the Advisory Committee on Immunization Practices (ACIP) to increase the risk of influenza-related complications.
We used a case-cohort design to compare cases of hospitalizations and deaths from 2009 pandemic A(H1N1) influenza occurring between April-July, 2009, with a cohort of the U.S. population estimated from the 2003-2006 National Health and Nutrition Examination Survey (NHANES); pregnant women and children <2 years old were excluded. For hospitalizations, we defined categories of relative weight by body mass index (BMI, kg/m(2)); for deaths, obesity or morbid obesity was recorded on medical charts, and death certificates. Odds ratio (OR) of being in each BMI category was determined; normal weight was the reference category. Overall, 361 hospitalizations and 233 deaths included information to determine BMI category and presence of ACIP-recognized medical conditions. Among >or=20 year olds, hospitalization was associated with being morbidly obese (BMI>or=40) for individuals with ACIP-recognized chronic conditions (OR = 4.9, 95% CI 2.4-9.9) and without ACIP-recognized chronic conditions (OR = 4.7, 95%CI 1.3-17.2). Among 2-19 year olds, hospitalization was associated with being underweight (BMI<or=5(th) percentile) among those with (OR = 12.5, 95%CI 3.4-45.5) and without (OR = 5.5, 95%CI 1.3-22.5) ACIP-recognized chronic conditions. Death was not associated with BMI category among individuals 2-19 years old. Among individuals aged >or=20 years without ACIP-recognized chronic medical conditions death was associated with obesity (OR = 3.1, 95%CI: 1.5-6.6) and morbid obesity (OR = 7.6, 95%CI 2.1-27.9).
Our findings support observations that morbid obesity may be associated with hospitalization and possibly death due to 2009 pandemic H1N1 infection. These complications could be prevented by early antiviral therapy and vaccination.
Population incidence of Guillain-Barré syndrome (GBS) is required to assess changes in GBS epidemiology, but published estimates of GBS incidence vary greatly depending on case ascertainment, ...definitions, and sample size. We performed a meta-analysis of articles on GBS incidence by searching Medline (1966-2009), Embase (1988-2009), Cinahl (1981-2009) and CABI (1973-2009) as well as article bibliographies. We included studies from North America and Europe with at least 20 cases, and used population-based data, subject matter experts to confirm GBS diagnosis, and an accepted GBS case definition. With these data, we fitted a random-effects negative binomial regression model to estimate age-specific GBS incidence. Of 1,683 nonduplicate citations, 16 met the inclusion criteria, which produced 1,643 cases and 152.7 million person-years of follow-up. GBS incidence increased by 20% for every 10-year increase in age; the risk of GBS was higher for males than females. The regression equation for calculating the average GBS rate per 100,000 person-years as a function of age in years was exp-12.0771 + 0.01813(age in years) × 100,000. Our findings provide a robust estimate of background GBS incidence in Western countries. Our regression model may be used in comparable populations to estimate the background age-specific rate of GBS incidence for future studies.
The World Health Organization considers an Ebola outbreak to have ended once 42 days have passed since the last possible exposure to a confirmed case. Benefits of a quick end-of-outbreak declaration, ...such as reductions in trade/travel restrictions, must be balanced against the chance of flare-ups from undetected residual cases. We show how epidemiological modelling can be used to estimate the surveillance level required for decision-makers to be confident that an outbreak is over. Results from a simple model characterizing an Ebola outbreak suggest that a surveillance sensitivity (i.e. case reporting percentage) of 79% is necessary for 95% confidence that an outbreak is over after 42 days without symptomatic cases. With weaker surveillance, unrecognized transmission may still occur: if the surveillance sensitivity is only 40%, then 62 days must be waited for 95% certainty. By quantifying the certainty in end-of-outbreak declarations, public health decision-makers can plan and communicate more effectively. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This issue is linked with the earlier theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ...ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics, an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
...surveillance systems must incorporate laboratory confirmation appropriately scaled for different diseases and risks. ...surveillance systems must be digitised, with unique health identifiers to ...connect individual-level data and with privacy safeguards. Benefits Implementation requirement Population-based Denominators for mortality rates and disease burden CRVS or sample registration system Laboratory confirmation Cases accurately tracked Capacity to scale testing and sequence pathogens Digital data Systems interconnected and privacy protected Unique health identifiers, standard metadata, web accessible Data transparency Visibility of all national threats by NPHIs and by WHO for transnational threats Automated reporting to NPHI with a subset to WHO and regional bodies Adequate financing Sustainable country-owned systems Invest US$1–4 per capita annually Table Core principles for integrated disease surveillance
The majority of drug-induced pancreatitis cases are mild to moderate in severity, but severe and even fatal cases can occur. Management of drug-induced pancreatitis requires withdrawal of the ...offending agent and supportive care.
This review focuses on differential diagnosis, clinical presentation, drug-mediated effects, treatments, and mechanisms of pancreatitis, with an emphasis on drug-induced pancreatitis.
Although only a minority of cases associated with acute pancreatitis are linked to drugs, clinical presentation and mechanisms of injury to the pancreas are not well understood by clinicians in terms of individual drug effects in the mediation or modulation of injury to the pancreas. In recent years, a large number of commonly prescribed medications has been linked to drug-induced pancreatitis pathogenesis. Although mechanisms are proposed, the exact cause of injury is either not well understood or controversial.
Future investigation into the mechanisms of pancreatitis and an appreciation by clinicians of the drugs commonly linked to the condition will help establish earlier diagnosis and quicker cessation of offending drugs in the treatment of drug-induced acute pancreatitis.
Following natural disasters, mismanagement of the dead has consequences for the psychological well-being of survivors. However, no technical guidelines currently exist for managing mass fatalities ...following large natural disasters. Existing methods of mass fatality management are not directly transferable as they are designed for transport accidents and acts of terrorism. Furthermore, no information is currently available about post-disaster management of the dead following previous large natural disasters.
After the tsunami disaster on 26 December 2004, we conducted three descriptive case studies to systematically document how the dead were managed in Thailand, Indonesia, and Sri Lanka. We considered the following parameters: body recovery and storage, identification, disposal of human remains, and health risks from dead bodies. We used participant observations as members of post-tsunami response teams, conducted semi-structured interviews with key informants, and collected information from published and unpublished documents. Refrigeration for preserving human remains was not available soon enough after the disaster, necessitating the use of other methods such as dry ice or temporary burial. No country had sufficient forensic capacity to identify thousands of victims. Rapid decomposition made visual identification almost impossible after 24-48 h. In Thailand, most forensic identification was made using dental and fingerprint data. Few victims were identified from DNA. Lack of national or local mass fatality plans further limited the quality and timeliness of response, a problem which was exacerbated by the absence of practical field guidelines or an international agency providing technical support.
Emergency response should not add to the distress of affected communities by inappropriately disposing of the victims. The rights of survivors to see their dead treated with dignity and respect requires practical guidelines and technical support. Mass fatality management following natural disasters needs to be informed by further field research and supported by a network of regional and international forensic institutes and agencies.
BackgroundThe mental health impact of the 2014–2016 Ebola epidemic has been described among survivors, family members and healthcare workers, but little is known about its impact on the general ...population of affected countries. We assessed symptoms of anxiety, depression and post-traumatic stress disorder (PTSD) in the general population in Sierra Leone after over a year of outbreak response.MethodsWe administered a cross-sectional survey in July 2015 to a national sample of 3564 consenting participants selected through multistaged cluster sampling. Symptoms of anxiety and depression were measured by Patient Health Questionnaire-4. PTSD symptoms were measured by six items from the Impact of Events Scale-revised. Relationships among Ebola experience, perceived Ebola threat and mental health symptoms were examined through binary logistic regression.ResultsPrevalence of any anxiety-depression symptom was 48% (95% CI 46.8% to 50.0%), and of any PTSD symptom 76% (95% CI 75.0% to 77.8%). In addition, 6% (95% CI 5.4% to 7.0%) met the clinical cut-off for anxiety-depression, 27% (95% CI 25.8% to 28.8%) met levels of clinical concern for PTSD and 16% (95% CI 14.7% to 17.1%) met levels of probable PTSD diagnosis. Factors associated with higher reporting of any symptoms in bivariate analysis included region of residence, experiences with Ebola and perceived Ebola threat. Knowing someone quarantined for Ebola was independently associated with anxiety-depression (adjusted OR (AOR) 2.3, 95% CI 1.7 to 2.9) and PTSD (AOR 2.095% CI 1.5 to 2.8) symptoms. Perceiving Ebola as a threat was independently associated with anxiety-depression (AOR 1.69 95% CI 1.44 to 1.98) and PTSD (AOR 1.86 95% CI 1.56 to 2.21) symptoms.ConclusionSymptoms of PTSD and anxiety-depression were common after one year of Ebola response; psychosocial support may be needed for people with Ebola-related experiences. Preventing, detecting, and responding to mental health conditions should be an important component of global health security efforts.
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