https://www.who.int/news/item/30-01-2020-statement-on-the-secondmeeting-of-the-international-health-regulations-( 2005)-emergency-committeeregarding-the-outbreak-of-novel-coronavirus-(2019-ncov) † https://www.who.int/publications/m/item/strategy-to-achieve-global-covid-19vaccination-by-mid-2022 § The strategy brief outlined updated goals, steps, targets, and operational priorities to guide countries, policy makers, civil society, manufacturers, and international organizations in their ongoing efforts through 2022. https://www.who.int/publications/m/item/ global-covid-19-vaccination-strategy-in-a-changing-world--july-2022-update ¶ Older adult definitions vary by country, ranging from persons aged ≥45 years to those aged ≥65 years.coverage with a complete COVID-19 vaccination series** for ** Definition of complete primary series might vary among countries and by vaccine product. National authorities have ultimate authority on scheduling decisions within their jurisdictions; however, WHO makes recommendations for COVID-19 vaccine products that have undergone Emergency Use Listing review. Vaccine fact sheets including these definitions according to WHO recommendations can be found at https://extranet.who.int/pqweb/vaccines/ vaccinescovid-19-vaccine-eul-issued.

Background On March 13, 2020, Uganda instituted COVID-19 symptom screening at its international airport, isolation and SARS-CoV-2 testing for symptomatic persons, and mandatory 14-day quarantine and testing of persons traveling through or from high-risk countries. On March 21, 2020, Uganda reported its first SARS-CoV-2 infection in a symptomatic traveler from Dubai. By April 12, 2020, 54 cases and 1257 contacts were identified. We describe the epidemiological, clinical, and transmission characteristics of these cases. Methods A confirmed case was laboratory-confirmed SARS-CoV-2 infection during March 21–April 12, 2020 in a resident of or traveler to Uganda. We reviewed case-person files and interviewed case-persons at isolation centers. We identified infected contacts from contact tracing records. Results Mean case-person age was 35 (±16) years; 34 (63%) were male. Forty-five (83%) had recently traveled internationally (‘imported cases’), five (9.3%) were known contacts of travelers, and four (7.4%) were community cases. Of the 45 imported cases, only one (2.2%) was symptomatic at entry. Among all case-persons, 29 (54%) were symptomatic at testing and five (9.3%) were pre-symptomatic. Among the 34 (63%) case-persons who were ever symptomatic, all had mild disease: 16 (47%) had fever, 13 (38%) reported headache, and 10 (29%) reported cough. Fifteen (28%) case-persons had underlying conditions, including three persons with HIV. An average of 31 contacts (range, 4–130) were identified per case-person. Five (10%) case-persons, all symptomatic, infected one contact each. Conclusion The first 54 case-persons with SARS-CoV-2 infection in Uganda primarily comprised incoming air travelers with asymptomatic or mild disease. Disease would likely not have been detected in these persons without the targeted testing interventions implemented in Uganda. Transmission was low among symptomatic persons and nonexistent from asymptomatic persons. Routine, systematic screening of travelers and at-risk persons, and thorough contact tracing will be needed for Uganda to maintain epidemic control.

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.

Introduction Crimean-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. Methods We 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). Results We 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 <1 km from grazing fields compared with 27 (48%) controls (ORM-H = 18, 95% CI = 3.2-∞) and 10 (71%) of 14 case-patients found ticks attached to their bodies ≤2 weeks before symptom onset, compared to 15 (27%) of 56 control-persons (ORM-H = 9.3, 95%CI = 1.9–46). Conclusions CCHF 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.

Introduction. Rift Valley fever (RVF) is a mosquito-borne viral zoonosis. The Uganda Ministry of Health received alerts of suspected viral haemorrhagic fever in humans from Kiruhura, Buikwe, Kiboga, and Mityana districts. Laboratory results from Uganda Virus Research Institute indicated that human cases were positive for Rift Valley fever virus (RVFV) by polymerase chain reaction. We investigated to determine the scope of outbreaks, identify exposure factors, and recommend evidence-based control and prevention measures. Methods. A suspected case was defined as a person with acute fever onset, negative malaria test result, and at least two of the following symptoms: headache, muscle or joint pain, bleeding, and any gastroenteritis symptom (nausea, vomiting, abdominal pain, diarrhoea) in a resident of Kiruhura, Buikwe, Mityana, and Kiboga districts from 1st October 2017 to 30th January 2018. A confirmed case was defined as a suspected case with laboratory confirmation by either detection of RVF nucleic acid by reverse-transcriptase polymerase chain reaction (RT-PCR) or demonstration of serum IgM or IgG antibodies by ELISA. Community case finding was conducted in all affected districts. In-depth interviews were conducted with human cases that were infected with RVF who included herdsmen and slaughterers/meat handlers to identify exposure factors for RVF infection. A total of 24 human and 362 animal blood samples were tested. Animal blood samples were purposively collected from farms that had reported stormy abortions in livestock and unexplained death of animals after a short illness (107 cattle, 83 goats, and 43 sheep). Convenient sampling for the wildlife (10 zebras, 1 topi, and 1 impala) was conducted to investigate infection in animals from Kiruhura, Buikwe, Mityana, and Kiboga districts. Human blood was tested for anti-RVFV IgM and IgG and animal blood for anti-RVFV IgG. Environmental assessments were conducted during the outbreaks in all the affected districts. Results. Sporadic RVF outbreaks occurred from mid-October 2017 to mid-January 2018 affecting humans, domestic animals, and wildlife. Human cases were reported from Kiruhura, Buikwe, Kiboga, and Mityana districts. Of the 24 human blood samples tested, anti-RVFV IgG was detected in 7 (29%) human samples; 1 human sample had detectable IgM only, and 6 had both IgM and IgG. Three of the seven confirmed human cases died among humans. Results from testing animal blood samples obtained from Kiruhura district indicated that 44% (64/146) cattle, 46% (35/76) goats, and 45% (9/20) sheep tested positive for RVF. Among wildlife, (1/10) zebras, (1/1) topi, and (1/1) impala tested positive for RVFV by serological tests. One blood sample from sheep in Kiboga district tested RVFV positive. All the human cases were exposed through contact or consumption of meat from infected animals. Conclusion. RVF outbreaks occurred in humans and animals in Kiruhura, Buikwe, Mityana, and Kiboga districts. Human cases were potentially infected through contact with infected animals and their products.

Background Kampala city slums, with one million dwellers living in poor sanitary conditions, frequently experience cholera outbreaks. On 6 January 2019, Rubaga Division notified the Uganda Ministry of Health of a suspected cholera outbreak in Sembule village. We investigated to identify the source and mode of transmission, and recommended evidence-based interventions. Methods We defined a suspected case as onset of profuse, painless, acute watery diarrhoea in a Kampala City resident (≥ 2 years) from 28 December 2018 to 11 February 2019. A confirmed case was a suspected case with Vibrio cholerae identified from the patient’s stool specimen by culture. We found cases by record review and active community case-finding. We conducted a case–control study in Sembule village, the epi-center of this outbreak, to compare exposures between confirmed case-persons and asymptomatic controls, individually matched by age group. We overlaid rainfall data with the epidemic curve to identify temporal patterns between rain and illnesses. We conducted an environmental assessment, interviewed village local council members, and tested water samples from randomly-selected households and water sources using culture and PCR to identify V. cholerae. Results We identified 50 suspected case-patients, with three deaths (case-fatality rate: 6.0%). Of 45 case-patients with stool samples tested, 22 were confirmed positive for V. cholerae O1, serotype Ogawa. All age groups were affected; persons aged 5–14 years had the highest attack rate (AR) (8.2/100,000). The epidemic curve showed several point-source outbreaks; cases repeatedly spiked immediately following rainfall. Sembule village had a token-operated water tap, which had broken down 1 month before the outbreak, forcing residents to obtain water from one of three wells (Wells A, B, C) or a public tap. Environmental assessment showed that residents emptied their feces into a drainage channel connected to Well C. Drinking water from Well C was associated with illness (ORM–H = 21, 95% CI 4.6–93). Drinking water from a public tap (ORM–H = 0.07, 95% CI 0.014–0.304) was protective. Water from a container in one of eight households sampled tested positive for V. cholerae; water from Well C had coliform counts ˃ 900/100 ml. Conclusions Drinking contaminated water from an unprotected well was associated with this cholera outbreak. We recommended emergency chlorination of drinking water, fixing the broken token tap, and closure of Well C.

Background On 23 February 2018, the Uganda Ministry of Health (MOH) declared a cholera outbreak affecting more than 60 persons in Kyangwali Refugee Settlement, Hoima District, bordering the Democratic Republic of Congo (DRC). We investigated to determine the outbreak scope and risk factors for transmission, and recommend evidence-based control measures. Methods We defined a suspected case as sudden onset of watery diarrhoea in any person aged ≥ 2 years in Hoima District, 1 February–9 May 2018. A confirmed case was a suspected case with Vibrio cholerae cultured from a stool sample. We found cases by active community search and record reviews at Cholera Treatment Centres. We calculated case-fatality rates (CFR) and attack rates (AR) by sub-county and nationality. In a case-control study, we compared exposure factors among case- and control-households. We estimated the association between the exposures and outcome using Mantel-Haenszel method. We conducted an environmental assessment in the refugee settlement, including testing samples of stream water, tank water, and spring water for presence of fecal coliforms. We tested suspected cholera cases using cholera rapid diagnostic test (RDT) kits followed by culture for confirmation. Results We identified 2122 case-patients and 44 deaths (CFR = 2.1%). Case-patients originating from Demographic Republic of Congo were the most affected (AR = 15/1000). The overall attack rate in Hoima District was 3.2/1000, with Kyangwali sub-county being the most affected (AR = 13/1000). The outbreak lasted 4 months, which was a multiple point-source. Environmental assessment showed that a stream separating two villages in Kyangwali Refugee Settlement was a site of open defecation for refugees. Among three water sources tested, only stream water was feacally-contaminated, yielding > 100 CFU/100 ml. Of 130 stool samples tested, 124 (95%) yielded V. cholerae by culture. Stream water was most strongly associated with illness (odds ratio [OR] = 14.2, 95% CI: 1.5–133), although tank water also appeared to be independently associated with illness (OR = 11.6, 95% CI: 1.4–94). Persons who drank tank and stream water had a 17-fold higher odds of illness compared with persons who drank from other sources (OR = 17.3, 95% CI: 2.2–137). Conclusions Our investigation demonstrated that this was a prolonged cholera outbreak that affected four sub-counties and two divisions in Hoima District, and was associated with drinking of contaminated stream water. In addition, tank water also appears to be unsafe. We recommended boiling drinking water, increasing latrine coverage, and provision of safe water by the District and entire High Commission for refugees.

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.