60,943 research outputs found

    Advancing detection and response capacities for emerging and re-emerging pathogens in Africa

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    Recurrent disease outbreaks caused by a range of emerging and resurging pathogens over the past decade reveal major gaps in public health preparedness, detection, and response systems in Africa. Underlying causes of recurrent disease outbreaks include inadequacies in the detection of new infectious disease outbreaks in the community, in rapid pathogen identification, and in proactive surveillance systems. In sub-Saharan Africa, where 70% of zoonotic outbreaks occur, there remains the perennial risk of outbreaks of new or re-emerging pathogens for which no vaccines or treatments are available. As the Ebola virus disease, COVID-19, and mpox (formerly known as monkeypox) outbreaks highlight, a major paradigm shift is required to establish an effective infrastructure and common frameworks for preparedness and to prompt national and regional public health responses to mitigate the effects of future pandemics in Africa

    Detection of infectious disease outbreaks in twenty-two fragile states, 2000-2010: a systematic review.

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    Fragile states are home to a sixth of the world's population, and their populations are particularly vulnerable to infectious disease outbreaks. Timely surveillance and control are essential to minimise the impact of these outbreaks, but little evidence is published about the effectiveness of existing surveillance systems. We did a systematic review of the circumstances (mode) of detection of outbreaks occurring in 22 fragile states in the decade 2000-2010 (i.e. all states consistently meeting fragility criteria during the timeframe of the review), as well as time lags from onset to detection of these outbreaks, and from detection to further events in their timeline. The aim of this review was to enhance the evidence base for implementing infectious disease surveillance in these complex, resource-constrained settings, and to assess the relative importance of different routes whereby outbreak detection occurs.We identified 61 reports concerning 38 outbreaks. Twenty of these were detected by existing surveillance systems, but 10 detections occurred following formal notifications by participating health facilities rather than data analysis. A further 15 outbreaks were detected by informal notifications, including rumours.There were long delays from onset to detection (median 29 days) and from detection to further events (investigation, confirmation, declaration, control). Existing surveillance systems yielded the shortest detection delays when linked to reduced barriers to health care and frequent analysis and reporting of incidence data.Epidemic surveillance and control appear to be insufficiently timely in fragile states, and need to be strengthened. Greater reliance on formal and informal notifications is warranted. Outbreak reports should be more standardised and enable monitoring of surveillance systems' effectiveness

    Bringing together emerging and endemic zoonoses surveillance: shared challenges and a common solution

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    Early detection of disease outbreaks in human and animal populations is crucial to the effective surveillance of emerging infectious diseases. However, there are marked geographical disparities in capacity for early detection of outbreaks, which limit the effectiveness of global surveillance strategies. Linking surveillance approaches for emerging and neglected endemic zoonoses, with a renewed focus on existing disease problems in developing countries, has the potential to overcome several limitations and to achieve additional health benefits. Poor reporting is a major constraint to the surveillance of both emerging and endemic zoonoses, and several important barriers to reporting can be identified: (i) a lack of tangible benefits when reports are made; (ii) a lack of capacity to enforce regulations; (iii) poor communication among communities, institutions and sectors; and (iv) complexities of the international regulatory environment. Redirecting surveillance efforts to focus on endemic zoonoses in developing countries offers a pragmatic approach that overcomes some of these barriers and provides support in regions where surveillance capacity is currently weakest. In addition, this approach addresses immediate health and development problems, and provides an equitable and sustainable mechanism for building the culture of surveillance and the core capacities that are needed for all zoonotic pathogens, including emerging disease threats

    Global Disease Detection Operations Center : tracking global outbreaks

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    The Global Disease Detection Operations Center monitors outbreaks across the globe and assesses their potential risk to the global community.The Operations Center was established in 2007 to address weaknesses or gaps in global public health surveillance and response capacity. The Operations Center monitors outbreaks from infectious and non- infectious causes, including public health events attributable to disasters, intoxications, and chemical, radiological, or nuclear events. Animal outbreaks of diseases that can be transmitted to humans (zoonotic diseases) are also monitored to assess whether emerging or re-emerging disease outbreaks among humans are occurring.Between March 2014 and February 2016, the Operations Center tracked over 235 outbreaks in 137 countries, in addition to the Ebola outbreaks. From MERS in the Middle East to yellow fever in West Africa to Zika virus in the Americas, these outbreaks justify global concern and have affected many lives.CS259997Bfactsheet_globaldiseasedetectionoperationscenter.pd

    Hand, foot and mouth disease in China: Evaluating an automated system for the detection of outbreaks

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    Objective To evaluate the performance of China's infectious disease automated alert and response system in the detection of outbreaks of hand, foot and mouth (HFM) disease. Methods We estimated size, duration and delay in reporting HFM disease outbreaks from cases notified between 1 May 2008 and 30 April 2010 and between 1 May 2010 and 30 April 2012, before and after automatic alert and response included HFM disease. Sensitivity, specificity and timeliness of detection of aberrations in the incidence of HFM disease outbreaks were estimated by comparing automated detections to observations of public health staff. Findings The alert and response system recorded 106 005 aberrations in the incidence of HFM disease between 1 May 2010 and 30 April 2012 - a mean of 5.6 aberrations per 100 days in each county that reported HFM disease. The response system had a sensitivity of 92.7% and a specificity of 95.0%. The mean delay between the reporting of the first case of an outbreak and detection of that outbreak by the response system was 2.1 days. Between the first and second study periods, the mean size of an HFM disease outbreak decreased from 19.4 to 15.8 cases and the mean interval between the onset and initial reporting of such an outbreak to the public health emergency reporting system decreased from 10.0 to 9.1 days. Conclusion The automated alert and response system shows good sensitivity in the detection of HFM disease outbreaks and appears to be relatively rapid. Continued use of this system should allow more effective prevention and limitation of such outbreaks in China

    Emerging viral infectious disease threat: Why Tanzania is not in a safe zone

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    Emerging diseases are global threat towards human existence. Every country is exposed to potentially emergence of infectious diseases. Several factor such as changes in ecology, climate and human demographics play different roles in a complex mechanism contributing to the occurrence of infectious diseases. Important aspects towards control in case of outbreaks are surveillance, preparedness and early response. Tanzania should therefore take opportunity of the calm situation currently present, to prepare. Except for HIV/AIDS, Tanzania has not experienced a major public health threat. However, the question is, is the country safe from emerging and re-emerging infectious diseases? In this article we try to explore the danger of emerging infectious disease (EID) epidemics in Tanzania and the risks attached if an outbreak is to occur. The aim is to formulate recommendations to the government, responsible authorities and general population of what can be done to improve the level of EID preparedness in the country. In conclusion, it is important to strengthen the capacity of community and healthcare staffs on how to respond to potential infectious disease outbreaks. Community-based surveillance systems should be incorporated into the national systems for early detection of public health events. It is also critical to enhance one health approach to increase cross-sectoral information sharing, surveillance and interventional strategies as regards to preparedness and response to disease outbreaks

    Dead Bird Clusters as an Early Warning System for West Nile Virus Activity

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    An early warning system for West Nile virus (WNV) outbreaks could provide a basis for targeted public education and surveillance activities as well as more timely larval and adult mosquito control. We adapted the spatial scan statistic for prospective detection of infectious disease outbreaks, applied the results to data on dead birds reported from New York City in 2000, and reviewed its utility in providing an early warning of WNV activity in 2001. Prospective geographic cluster analysis of dead bird reports may provide early warning of increasing viral activity in birds and mosquitoes, allowing jurisdictions to triage limited mosquito-collection and laboratory resources and more effectively prevent human disease caused by the virus. This adaptation of the scan statistic could also be useful in other infectious disease surveillance systems, including that for bioterrorism

    Using GIS to create synthetic disease outbreaks

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    BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance
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