Syndromic surveillance during 2022 Uganda Martyrs’ commemoration
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ABSTRACT:
SUBMITTER: Ninsiima M
PROVIDER: S-EPMC10810525 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundSheep and goat pox (SGP) caused by sheep poxvirus (SPV) and goat poxvirus (GPV) respectively; are transboundary and World Organisation for Animal Health (WOAH)-notifiable viral diseases. There is barely any coherent information about the distribution and prevalence of SGP for Uganda. We therefore conducted this study to describe the temporal and spatial distribution of SGP suspected outbreaks in Uganda for the period 2011-2020 as well as serologically confirm presence of SGP antibodies in suspected SGP outbreaks reported in 2021-2022.ResultsThirty-seven [37] SGP outbreaks were reported across the country during the study period. North-eastern region [that comprises of Karamoja region] had the highest number of outbreaks [n = 17, 45%]; followed by Central [n = 9, 2.4%], Northern [n = 8, 2.2%] and Western region [n = 3, 0.08%]. Reports from district veterinary personnel indicate that the prevalence of; and mortality rate and case fatality rate associated with SGP were 0.06%, 0.02% and 32% respectively. There was a steady increase in the number of reported SGP outbreaks [x̄ = 4] over the study period. Seropositivity of SGPV antibodies in outbreak sheep and goats that were investigated during the study period [2021-2022] was [n = 41, 27%, 95 CI;] CONCLUSION: Our analyses of SGPV passive and active reports indicate that SGP is present in Uganda with a decade long average of four outbreaks per annum. During this period, about a third of all SGPV-clinically infected animals died. SPG is therefore a major constraint to small ruminant health and productivity in Uganda. Introduction of animals from infected herds and breach in farm biosecurity were the most important predictors of SGP outbreaks. In addition to the already existing SGP commercial vaccines, small ruminant screening for SGPV before introducing them to naïve herds and ensuring on farm biosecurity should be part of the SGP control tool pack for Ugandan small ruminant farmers.
| S-EPMC10612334 | biostudies-literature
Project description:On September 20, 2022, an Ebola Disease (EBOD) outbreak was declared in Mubende district, Central Uganda. Following a rapid surge in the number of cases and mortality, the Government of Uganda imposed a lockdown in the two most affected districts, Mubende and Kassanda. We describe the trends in EBOD incidence and mortality nationally and in the two districts before and during the lockdown and the lessons learned during the epidemic response. We retrieved data from the Ministry of Health situation reports from September 20, 2022, when the EBOD outbreak was declared until November 26, 2022, when the lockdown ended. We graphed trends in EBOD morbidity and mortality during a 3-week and 6-week lockdown, computed the EBOD case fatality rate, and summarized the major lessons learned during the epidemic response. We found case fatality rate during the pre-lockdown, 3-week lockdown, and 6-week lockdown period was 37.9% (22/58), 39.3% (53/135), and 38.7% (55/142), respectively. In the early weeks of the lockdown, EBOD incidence and mortality increased nationally and in Kassanda district while Mubende district registered a decline in incidence and stagnation in mortality. With the extension of the lockdown to six weeks, the EBOD incidence and mortality during the 4-6-week lockdown declined compared to the pre-lockdown period. In conclusion, the EBOD incidence and mortality remained higher in the early weeks of the lockdown than during the pre-lockdown period nationally and in one of the two districts. With extended lockdown, incidence and mortality dropped in the 4-6-week period than the pre-lockdown period. Therefore, reliance on known public health measures to control an EBOD outbreak is important.
| S-EPMC10745136 | biostudies-literature
Project description:ImportanceRespiratory pathogens cause high rates of morbidity and mortality globally and have high pandemic potential. During the SARS-CoV-2 pandemic, influenza surveillance was significantly interrupted because of resources being diverted to SARS-CoV-2 testing and sequencing. Based on recommendations from the World Health Organization, the Uganda Virus Research Institute, National Influenza Center laboratory integrated SARS-CoV-2 testing and genomic sequencing into the influenza surveillance program. We describe the results of influenza and SARS-CoV-2 testing of samples collected from 16 sentinel surveillance sites located throughout Uganda as well as SARS-CoV-2 testing and sequencing in other health centers. The surveillance system showed that both SARS-CoV-2 and influenza can be monitored in communities at the national level. The integration of SARS-CoV-2 detection and genomic surveillance into the influenza surveillance program will help facilitate the timely release of SARS-CoV-2 information for COVID-19 pandemic mitigation and provide important information regarding the persistent threat of influenza.
| S-EPMC10715035 | biostudies-literature
Project description:BackgroundAlthough an increasing number of studies are documenting uses of syndromic surveillance by front line public health, few detail the value added from linking syndromic data to public health decision-making. This study seeks to understand how syndromic data informed specific public health actions during the 2009 H1N1 pandemic.MethodsSemi-structured telephone interviews were conducted with participants from Ontario's public health departments, the provincial ministry of health and federal public health agency to gather information about syndromic surveillance systems used and the role of syndromic data in informing specific public health actions taken during the pandemic. Responses were compared with how the same decisions were made by non-syndromic surveillance users.ResultsFindings from 56 interviews (82% response) show that syndromic data were most used for monitoring virus activity, measuring impact on the health care system and informing the opening of influenza assessment centres in several jurisdictions, and supporting communications and messaging, rather than its intended purpose of early outbreak detection. Syndromic data had limited impact on decisions that involved the operation of immunization clinics, school closures, sending information letters home with school children or providing recommendations to health care providers. Both syndromic surveillance users and non-users reported that guidance from the provincial ministry of health, communications with stakeholders and vaccine availability were driving factors in these public health decisions.ConclusionsSyndromic surveillance had limited use in decision-making during the 2009 H1N1 pandemic in Ontario. This study provides insights into the reasons why this occurred. Despite this, syndromic data were valued for providing situational awareness and confidence to support public communications and recommendations. Developing an understanding of how syndromic data are utilized during public health events provides valuable evidence to support future investments in public health surveillance.
| S-EPMC3539916 | biostudies-literature
Project description:BACKGROUND: Public health surveillance is the monitoring of data to detect and quantify unusual health events. Monitoring pre-diagnostic data, such as emergency department (ED) patient chief complaints, enables rapid detection of disease outbreaks. There are many sources of variation in such data; statistical methods need to accurately model them as a basis for timely and accurate disease outbreak methods. METHODS: Our new methods for modeling daily chief complaint counts are based on a seasonal-trend decomposition procedure based on loess (STL) and were developed using data from the 76 EDs of the Indiana surveillance program from 2004 to 2008. Square root counts are decomposed into inter-annual, yearly-seasonal, day-of-the-week, and random-error components. Using this decomposition method, we develop a new synoptic-scale (days to weeks) outbreak detection method and carry out a simulation study to compare detection performance to four well-known methods for nine outbreak scenarios. RESULT: The components of the STL decomposition reveal insights into the variability of the Indiana ED data. Day-of-the-week components tend to peak Sunday or Monday, fall steadily to a minimum Thursday or Friday, and then rise to the peak. Yearly-seasonal components show seasonal influenza, some with bimodal peaks.Some inter-annual components increase slightly due to increasing patient populations. A new outbreak detection method based on the decomposition modeling performs well with 90 days or more of data. Control limits were set empirically so that all methods had a specificity of 97%. STL had the largest sensitivity in all nine outbreak scenarios. The STL method also exhibited a well-behaved false positive rate when run on the data with no outbreaks injected. CONCLUSION: The STL decomposition method for chief complaint counts leads to a rapid and accurate detection method for disease outbreaks, and requires only 90 days of historical data to be put into operation. The visualization tools that accompany the decomposition and outbreak methods provide much insight into patterns in the data, which is useful for surveillance operations.
| S-EPMC2680402 | biostudies-other
Project description:The 2002 Olympic Winter Games were held in Utah from February 8 to March 16, 2002. Following the terrorist attacks on September 11, 2001, and the anthrax release in October 2001, the need for bioterrorism surveillance during the Games was paramount. A team of informaticists and public health specialists from Utah and Pittsburgh implemented the Real-time Outbreak and Disease Surveillance (RODS) system in Utah for the Games in just seven weeks. The strategies and challenges of implementing such a system in such a short time are discussed. The motivation and cooperation inspired by the 2002 Olympic Winter Games were a powerful driver in overcoming the organizational issues. Over 114,000 acute care encounters were monitored between February 8 and March 31, 2002. No outbreaks of public health significance were detected. The system was implemented successfully and operational for the 2002 Olympic Winter Games and remains operational today.
| S-EPMC264432 | biostudies-literature
Project description:Syndromic surveillance is increasingly used to signal unusual illness events. To validate data-source selection, we retrospectively investigated the extent to which 6 respiratory syndromes (based on different medical registries) reflected respiratory pathogen activity. These syndromes showed higher levels in winter, which corresponded with higher laboratory counts of Streptococcus pneumoniae, respiratory syncytial virus, and influenza virus. Multiple linear regression models indicated that most syndrome variations (up to 86%) can be explained by counts of respiratory pathogens. Absenteeism and pharmacy syndromes might reflect nonrespiratory conditions as well. We also observed systematic syndrome elevations in the fall, which were unexplained by pathogen counts but likely reflected rhinovirus activity. Earliest syndrome elevations were observed in absenteeism data, followed by hospital data (+1 week), pharmacy/general practitioner consultations (+2 weeks), and deaths/laboratory submissions (test requests) (+3 weeks). We conclude that these syndromes can be used for respiratory syndromic surveillance, since they reflect patterns in respiratory pathogen activity.
| S-EPMC2600280 | biostudies-literature
Project description:BackgroundSyndromic surveillance provides public health intelligence to aid in early warning and monitoring of public health impacts (e.g. seasonal influenza), or reassurance when an impact has not occurred. Using information collected during routine patient care, syndromic surveillance can be based on signs/symptoms/preliminary diagnoses. This approach makes syndromic surveillance much timelier than surveillance requiring laboratory confirmed diagnoses. The provision of healthcare services and patient access to them varies globally. However, emergency departments (EDs) exist worldwide, providing unscheduled urgent care to people in acute need. This provision of care makes ED syndromic surveillance (EDSyS) a potentially valuable tool for public health surveillance internationally. The objective of this study was to identify and describe the key characteristics of EDSyS systems that have been established and used globally.MethodsWe systematically reviewed studies published in peer review journals and presented at International Society of Infectious Disease Surveillance conferences (up to and including 2017) to identify EDSyS systems which have been created and used for public health purposes. Search criteria developed to identify "emergency department" and "syndromic surveillance" were applied to NICE healthcare, Global Health and Scopus databases.ResultsIn total, 559 studies were identified as eligible for inclusion in the review, comprising 136 journal articles and 423 conference abstracts/papers. From these studies we identified 115 EDSyS systems in 15 different countries/territories across North America, Europe, Asia and Australasia. Systems ranged from local surveillance based on a single ED, to comprehensive national systems. National EDSyS systems were identified in 8 countries/territories: 2 reported inclusion of ≥85% of ED visits nationally (France and Taiwan).ConclusionsEDSyS provides a valuable tool for the identification and monitoring of trends in severe illness. Technological advances, particularly in the emergency care patient record, have enabled the evolution of EDSyS over time. EDSyS reporting has become closer to 'real-time', with automated, secure electronic extraction and analysis possible on a daily, or more frequent basis. The dissemination of methods employed and evidence of successful application to public health practice should be encouraged to support learning from best practice, enabling future improvement, harmonisation and collaboration between systems in future.Prospero numberCRD42017069150 .
| S-EPMC7724621 | biostudies-literature
Project description:AimsMitigation actions during the COVID-19 pandemic may impact mental health and suicide in general populations. We aimed to analyse the evolution in suicide deaths from 2020 to March 2022 in France.MethodsUsing free-text medical causes in death certificates, we built an algorithm, which aimed to identify suicide deaths. We measured its retrospective performances by comparing suicide deaths identified using the algorithm with deaths which had either a Tenth revision of the International Classification of Diseases (ICD-10) code for 'intentional self-harm' or for 'external cause of undetermined intent' as the underlying cause. The number of suicide deaths from January 2020 to March 2022 was then compared with the expected number estimated using a generalized additive model. The difference and the ratio between the observed and expected number of suicide deaths were calculated on the three lockdown periods and for periods between lockdowns and after the third one. The analysis was stratified by age group and gender.ResultsThe free-text algorithm demonstrated high performances. From January 2020 to mid-2021, suicide mortality declined during France's three lockdowns, particularly in men. During the periods between and after the two first lockdowns, suicide mortality remained comparable to the expected values, except for men over 85 years old and in 65-84 year-old age group, where a small number of excess deaths was observed in the weeks following the end of first lockdown, and for men aged 45-64 years old, where the decline continued after the second lockdown ended. After the third lockdown until March 2022, an increase in suicide mortality was observed in 18-24 year-old age group for both genders and in men aged 65-84 years old, while a decrease was observed in the 25-44 year-old age group.ConclusionsThis study highlighted the absence of an increase in suicide mortality during France's COVID-19 pandemic and a substantial decline during lockdown periods, something already observed in other countries. The increase in suicide mortality observed in 18-24 year-old age group and in men aged 65-84 years old from mid-2021 to March 2022 suggests a prolonged impact of COVID-19 on mental health, also described on self-harm hospitalizations and emergency department's attendances in France. Further studies are required to explain the factors for this change. Reactive monitoring of suicide mortality needs to be continued since mental health consequences and the increase in suicide mortality may be continued in the future with the international context.
| S-EPMC10130823 | biostudies-literature
Project description:The use of natural language data for animal population surveillance represents a valuable opportunity to gather information about potential disease outbreaks, emerging zoonotic diseases, or bioterrorism threats. In this study, we evaluate machine learning methods for conducting syndromic surveillance using free-text veterinary necropsy reports. We train a system to detect if a necropsy report from the Wisconsin Veterinary Diagnostic Laboratory contains evidence of gastrointestinal, respiratory, or urinary pathology. We evaluate the performance of several machine learning algorithms including deep learning with a long short-term memory network. Although no single algorithm was superior, random forest using feature vectors of TF-IDF statistics ranked among the top-performing models with F1 scores of 0.923 (gastrointestinal), 0.960 (respiratory), and 0.888 (urinary). This model was applied to over 33,000 necropsy reports and was used to describe temporal and spatial features of diseases within a 14-year period, exposing epidemiological trends and detecting a potential focus of gastrointestinal disease from a single submitting producer in the fall of 2016.
| S-EPMC7001958 | biostudies-literature