Prompt response to a cross-border plague outbreak in Zombo District, minimized spread, Uganda, March 2019

Introduction: Plague, which is caused by the bacterium Yersinia pestis, is a priority zoonotic disease targeted for elimination in Uganda. On 6 March 2019, the Uganda Ministry of Health was notified of a patient in Zombo District with clinical presentation similar to pneumonic plague, and a positive plague rapid diagnostic test (RDT). We determined the scope of the outbreak, determined the mode of transmission, and recommended evidence-based control and prevention measures. Methods: A suspected pneumonic plague case was one with two or more of the following signs and symptoms: cough (bloody or wet), chest pain, difficulty in breathing, or fever in a resident of Zombo District during February 1-March 31, 2019. A confirmed case was a suspected case testing positive for Yersinia pestis by rapid diagnostic test, culture or serology. We actively searched for case-patients, traced contacts and took samples as appropriate. We performed descriptive epidemiology of the outbreak. Results: We identified one suspected and one confirmed pneumonic plague case. On February 26, 2019, a 4-year-old boy was buried in DRC near the Uganda border after succumbing to bubonic plague. Case-patient A (35-year-old mother to the boy), fell ill with suspected pneumonic plague while attending to him. She was referred to a health facility in Uganda on February 28 but died on arrival. On March 4, Case-patient B (23-year-old sister to Case-patient A), presented with pneumonic plague symptoms to the same Uganda facility and tested plague-positive by RDT, culture, and serological tests. Contacts (n=114) were traced and given prophylaxis; no new cases were reported. Conclusion: This fatal plague outbreak started as bubonic and later manifested as pneumonic. There was cross-border spread from DRC to Uganda with no cross-border efforts at prevention and control. Person-to-person transmission appears to have occurred. The quick and effective response likely minimized spread

Temporal, spatial and household dynamics of Typhoid fever in Kasese district, Uganda

<div><p>Typhoid fever affects 21 million people globally, 1% of whom succumb to the disease. The social, economic and public health consequences of this disease disproportionately affect people in Africa and Asia. In order to design context specific prevention strategies, we need to holistically characterise outbreaks in these settings. In this study, we used retrospective data (2013–2016) at national and district level to characterise temporal and spatial dynamics of Typhoid fever outbreaks using time series and spatial analysis. We then selected cases matched with controls to investigate household socio-economic drivers using a conditional logistic regression model, and also developed a Typhoid fever outbreak-forecasting framework. The incidence rate of Typhoid fever at national and district level was ~ 160 and 60 cases per 100,000 persons per year, respectively, predominantly in urban areas. In Kasese district, Bwera sub-county registered the highest incidence rate, followed by Kisinga, Kitholhu and Nyakiyumbu sub-counties. The male-female case ratio at district level was at 1.68 and outbreaks occurred between the 20^th and 40^th week (May and October) each year following by seven weeks of precipitation. Our forecasting framework predicted outbreaks better at the district level rather than national. We identified a temporal window associated with Typhoid fever outbreaks in Kasese district, which is preceded by precipitation, flooding and displacement of people. We also observed that areas with high incidence of Typhoid fever also had high environmental contamination with limited water treatment. Taken together with the forecasting framework, this knowledge can inform the development of specific control and preparedness strategies at district and national level.</p></div

Molecular Detection of <i>Cryptosporidium</i> Species in Wildlife and Humans at the Wildlife-Human Interface around Queen Elizabeth National Park, Uganda

To date, information on Cryptosporidium spp. infection status among people and wild animals living at the wildlife-human interface such as Queen Elizabeth National Park (QENP) is scarce. The aim of this study is to document the molecular detection of Cryptosporidium spp. in wild animals, and people, around QENP in the Kasese District. A total of 308 patients from four health centres and 252 wildlife animals from six species across 13 sampling areas were analysed microscopically and with PCR for Cryptosporidium spp. detection. The parasitological and molecular prevalence of Cryptosporidium spp. in humans was 40% and 53%, respectively; Kasenyi Health Centre recorded the highest percentage of positive stool samples for both tests. Wildlife species had an overall molecular percentage positivity of 30.16%; however, considering individual animal species that were sampled, the Waterbucks had the highest positivity rate, that is, 54.54%. All the samples were confirmed as genus Cryptosporidium with less species discrimination as our PCR target was a short fragment. There is a need to investigate the risk factors that predispose to high Cryptosporidium infection in the study area, especially in Kasenyi. In-depth investigation of the genetic diversity of Cryptosporidium spp. circulating at the human, livestock, and wildlife interface is imperative in devising disease management strategies

Data from: Temporal, spatial and household dynamics of typhoid fever in Kasese district, Uganda

Typhoid fever affects 21 million people globally, 1% of whom succumb to the disease. The social, economic and public health consequences of this disease disproportionately affect people in Africa and Asia. In order to design context specific prevention strategies, we need to holistically characterise outbreaks in these settings. Here we used retrospective data (2013-2016) at national and district level to characterize temporal and spatial dynamics of typhoid fever outbreaks using time series and spatial analysis. We then selected cases matched with controls to investigate household socio-economic drivers using a conditional logistic regression model, in addition to develop a typhoid outbreak-forecasting framework. The incidence rate of typhoid fever at national and district level was ~ 160 and 60 cases per 100,000 persons per year, respectively, predominantly in urban areas. Bwera sub-county registered the highest incidence rate, followed by Kisinga, Kitholhu and Nyakiyumbu sub-counties. The male-female case ratio at district level was at 1.68 and outbreaks occurred between the 20th and 40th week (May and October) each year preceded by seven weeks of precipitation. Our forecasting framework predicts outbreaks better at the district rather than at the national level. We have identified a temporal window associated with typhoid fever outbreaks in Kasese district, which is preceded by precipitation, flooding and displacement of people. We also observed that high typhoid incidence areas also had high environmental contamination with limited water treatment. Taken together with the forecasting framework, this knowledge can inform the development of specific control and preparedness strategies at district and national levels.Mirembe, Bernadette Basuta et al. (2019), Data from: Temporal, spatial and household dynamics of typhoid fever in Kasese district, Uganda, Dryad, Dataset, https://doi.org/10.5061/dryad.fh8k35

Sporadic outbreaks of crimean-congo haemorrhagic fever in Uganda, July 2018-January 2019.

IntroductionCrimean-Congo haemorrhagic fever (CCHF) is a tick-borne, zoonotic viral disease that causes haemorrhagic symptoms. Despite having eight confirmed outbreaks between 2013 and 2017, all within Uganda's 'cattle corridor', no targeted tick control programs exist in Uganda to prevent disease. During a seven-month-period from July 2018-January 2019, the Ministry of Health confirmed multiple independent CCHF outbreaks. We investigated to identify risk factors and recommend interventions to prevent future outbreaks.MethodsWe defined a confirmed case as sudden onset of fever (≥37.5°C) with ≥4 of the following signs and symptoms: anorexia, vomiting, diarrhoea, headache, abdominal pain, joint pain, or sudden unexplained bleeding in a resident of the affected districts who tested positive for Crimean-Congo haemorrhagic fever virus (CCHFv) by RT-PCR from 1 July 2018-30 January 2019. We reviewed medical records and performed active case-finding. We conducted a case-control study and compared exposures of case-patients with age-, sex-, and sub-county-matched control-persons (1:4).ResultsWe identified 14 confirmed cases (64% males) with five deaths (case-fatality rate: 36%) from 11 districts in western and central region. Of these, eight (73%) case-patients resided in Uganda's 'cattle corridor'. One outbreak involved two case-patients and the remainder involved one. All case-patients had fever and 93% had unexplained bleeding. Case-patients were aged 6-36 years, with persons aged 20-44 years more affected (AR: 7.2/1,000,000) than persons ≤19 years (2.0/1,000,000), p = 0.015. Most (93%) case-patients had contact with livestock ≤2 weeks before symptom onset. Twelve (86%) lived ConclusionsCCHF outbreaks occurred sporadically during 2018-2019, both within and outside 'cattle corridor' districts of Uganda. Most cases were associated with tick exposure. The Ministry of Health should partner with the Ministry of Agriculture, Animal Industry and Fisheries to develop joint nationwide tick control programs and strategies with shared responsibilities through a One Health approach

Mpox in Children and Adolescents during Multicountry Outbreak, 2022–2023

The 2022–2023 mpox outbreak predominantly affected adult men; 1.3% of reported cases were in children and adolescents <18 years of age. Analysis of global surveillance data showed 1 hospital intensive care unit admission and 0 deaths in that age group. Transmission routes and clinical manifestations varied across age subgroups

The World Health Organization’s public health intelligence activities during the COVID-19 pandemic response, December 2019 to December 2021

The coronavirus disease (COVID-19) presented a unique opportunity for the World Health Organization (WHO) to utilise public health intelligence (PHI) for pandemic response. WHO systematically captured mainly unstructured information (e.g. media articles, listservs, community-based reporting) for public health intelligence purposes. WHO used the Epidemic Intelligence from Open Sources (EIOS) system as one of the information sources for PHI. The processes and scope for PHI were adapted as the pandemic evolved and tailored to regional response needs. During the early months of the pandemic, media monitoring complemented official case and death reporting through the International Health Regulations mechanism and triggered alerts. As the pandemic evolved, PHI activities prioritised identifying epidemiological trends to supplement the information available through indicator-based surveillance reported to WHO. The PHI scope evolved over time to include vaccine introduction, emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, unusual clinical manifestations and upsurges in cases, hospitalisation and death incidences at subnational levels. Triaging the unprecedented high volume of information challenged surveillance activities but was managed by collaborative information sharing. The evolution of PHI activities using multiple sources in WHO’s response to the COVID-19 pandemic illustrates the future directions in which PHI methodologies could be developed and used.</jats:p

WHO Global Situational Alert System: a mixed methods multistage approach to identify country-level COVID-19 alerts

Background Globally, since 1 January 2020 and as of 24 January 2023, there have been over 664 million cases of COVID-19 and over 6.7 million deaths reported to WHO. WHO developed an evidence-based alert system, assessing public health risk on a weekly basis in 237 countries, territories and areas from May 2021 to June 2022. This aimed to facilitate the early identification of situations where healthcare capacity may become overstretched.Methods The process involved a three-stage mixed methods approach. In the first stage, future deaths were predicted from the time series of reported cases and deaths to produce an initial alert level. In the second stage, this alert level was adjusted by incorporating a range of contextual indicators and accounting for the quality of information available using a Bayes classifier. In the third stage, countries with an alert level of ‘High’ or above were added to an operational watchlist and assistance was deployed as needed.Results Since June 2021, the system has supported the release of more than US$27 million from WHO emergency funding, over 450 000 rapid antigen diagnostic testing kits and over 6000 oxygen concentrators. Retrospective evaluation indicated that the first two stages were needed to maximise sensitivity, where 44% (IQR 29%–67%) of weekly watchlist alerts would not have been identified using only reported cases and deaths. The alerts were timely and valid in most cases; however, this could only be assessed on a non-representative sample of countries with hospitalisation data available.Conclusions The system provided a standardised approach to monitor the pandemic at the country level by incorporating all available data on epidemiological analytics and contextual assessments. While this system was developed for COVID-19, a similar system could be used for future outbreaks and emergencies, with necessary adjustments to parameters and indicators