Uganda's experience in Ebola virus disease outbreak preparedness, 2018-2019.

BACKGROUND: Since the declaration of the 10th Ebola Virus Disease (EVD) outbreak in DRC on 1st Aug 2018, several neighboring countries have been developing and implementing preparedness efforts to prevent EVD cross-border transmission to enable timely detection, investigation, and response in the event of a confirmed EVD outbreak in the country. We describe Uganda's experience in EVD preparedness. RESULTS: On 4 August 2018, the Uganda Ministry of Health (MoH) activated the Public Health Emergency Operations Centre (PHEOC) and the National Task Force (NTF) for public health emergencies to plan, guide, and coordinate EVD preparedness in the country. The NTF selected an Incident Management Team (IMT), constituting a National Rapid Response Team (NRRT) that supported activation of the District Task Forces (DTFs) and District Rapid Response Teams (DRRTs) that jointly assessed levels of preparedness in 30 designated high-risk districts representing category 1 (20 districts) and category 2 (10 districts). The MoH, with technical guidance from the World Health Organisation (WHO), led EVD preparedness activities and worked together with other ministries and partner organisations to enhance community-based surveillance systems, develop and disseminate risk communication messages, engage communities, reinforce EVD screening and infection prevention measures at Points of Entry (PoEs) and in high-risk health facilities, construct and equip EVD isolation and treatment units, and establish coordination and procurement mechanisms. CONCLUSION: As of 31 May 2019, there was no confirmed case of EVD as Uganda has continued to make significant and verifiable progress in EVD preparedness. There is a need to sustain these efforts, not only in EVD preparedness but also across the entire spectrum of a multi-hazard framework. These efforts strengthen country capacity and compel the country to avail resources for preparedness and management of incidents at the source while effectively cutting costs of using a "fire-fighting" approach during public health emergencies

Marburg virus disease outbreak in Kween District Uganda, 2017: Epidemiological and laboratory findings.

INTRODUCTION: In October 2017, a blood sample from a resident of Kween District, Eastern Uganda, tested positive for Marburg virus. Within 24 hour of confirmation, a rapid outbreak response was initiated. Here, we present results of epidemiological and laboratory investigations. METHODS: A district task force was activated consisting of specialised teams to conduct case finding, case management and isolation, contact listing and follow up, sample collection and testing, and community engagement. An ecological investigation was also carried out to identify the potential source of infection. Virus isolation and Next Generation sequencing were performed to identify the strain of Marburg virus. RESULTS: Seventy individuals (34 MVD suspected cases and 36 close contacts of confirmed cases) were epidemiologically investigated, with blood samples tested for MVD. Only four cases met the MVD case definition; one was categorized as a probable case while the other three were confirmed cases. A total of 299 contacts were identified; during follow- up, two were confirmed as MVD. Of the four confirmed and probable MVD cases, three died, yielding a case fatality rate of 75%. All four cases belonged to a single family and 50% (2/4) of the MVD cases were female. All confirmed cases had clinical symptoms of fever, vomiting, abdominal pain and bleeding from body orifices. Viral sequences indicated that the Marburg virus strain responsible for this outbreak was closely related to virus strains previously shown to be circulating in Uganda. CONCLUSION: This outbreak of MVD occurred as a family cluster with no additional transmission outside of the four related cases. Rapid case detection, prompt laboratory testing at the Uganda National VHF Reference Laboratory and presence of pre-trained, well-prepared national and district rapid response teams facilitated the containment and control of this outbreak within one month, preventing nationwide and global transmission of the disease

Cholera epidemic amidst the COVID-19 pandemic in Moroto district, Uganda: Hurdles and opportunities for control.

IntroductionOn 21st March 2020, the first COVID-19 case was detected in Uganda and a COVID-19 pandemic declared. On the same date, a nationwide lockdown was instituted in response to the pandemic. Subsequently, more cases were detected amongst the returning international travelers as the disease continued to spread across the country. On May 14th, 2020, a cholera epidemic was confirmed in Moroto district at a time when the district had registered several COVID-19 cases and was in lockdown. This study aimed to describe the cholera epidemic and response activities during the COVID-19 pandemic as well as the hurdles and opportunities for cholera control encountered during the response.Materials and methodsIn a cross-sectional study design, we reviewed Moroto district's weekly epidemiological records on cholera and COVID-19 from April to July 2020. We obtained additional information through a review of the outbreak investigation and control reports. Data were analyzed and presented in frequencies, proportions, attack rates, case fatality rates, graphs, and maps.ResultsAs of June 28th, 2020, 458 cases presenting with severe diarrhea and/or vomiting were line listed in Moroto district. The most affected age group was 15-30 years, 30.1% (138/458). The females, 59.0% [270/458], were the majority. The Case Fatality Rate (CFR) was 0.4% (2/458). Whereas home use of contaminated water following the vandalization of the only clean water source in Natapar Kocuc village, Moroto district, could have elicited the epidemic, implementing COVID-19 preventive and control measures presented some hurdles and opportunities for cholera control. The significant hurdles were observing the COVID-19 control measures such as social distancing, wearing of masks, and limited time in the community due to the need to observe curfew rules starting at 6.00 pm. The opportunities from COVID-19 measures complementary to cholera control measures included frequent hand washing, travel restrictions within the district & surrounding areas, and closure of markets.ConclusionCOVID-19 preventive and control measures such as social distancing, wearing of masks, and curfew rules may be a hurdle to cholera control whereas frequent hand washing, travel restrictions within the district & surrounding areas, and closure of markets may present opportunities for cholera control. Other settings experiencing concurrent cholera and COVID-19 outbreaks can borrow lessons from this study

Identifying cholera "hotspots" in Uganda: An analysis of cholera surveillance data from 2011 to 2016

<div><p>Background</p><p>Despite advance in science and technology for prevention, detection and treatment of cholera, this infectious disease remains a major public health problem in many countries in sub-Saharan Africa, Uganda inclusive. The aim of this study was to identify cholera hotspots in Uganda to guide the development of a roadmap for prevention, control and elimination of cholera in the country.</p><p>Methodology/Principle findings</p><p>We obtained district level confirmed cholera outbreak data from 2011 to 2016 from the Ministry of Health, Uganda. Population and rainfall data were obtained from the Uganda Bureau of Statistics, and water, sanitation and hygiene data from the Ministry of Water and Environment. A spatial scan test was performed to identify the significantly high risk clusters. Cholera hotspots were defined as districts whose center fell within a significantly high risk cluster or where a significantly high risk cluster was completely superimposed onto a district. A zero-inflated negative binomial regression model was employed to identify the district level risk factors for cholera. In total 11,030 cases of cholera were reported during the 6-year period. 37(33%) of 112 districts reported cholera outbreaks in one of the six years, and 20 (18%) districts experienced cholera at least twice in those years. We identified 22 districts as high risk for cholera, of which 13 were near a border of Democratic Republic of Congo (DRC), while 9 districts were near a border of Kenya. The relative risk of having cholera inside the high-risk districts (hotspots) were 2 to 22 times higher than elsewhere in the country. In total, 7 million people were within cholera hotspots. The negative binomial component of the ZINB model shows people living near a lake or the Nile river were at increased risk for cholera (incidence rate ratio, IRR = 0.98, 95% CI: 0.97 to 0.99, p < .01); people living near the border of DRC/Kenya or higher incidence rate in the neighboring districts were increased risk for cholera in a district (IRR = 0.99, 95% CI: 0.98 to 1.00, p = .02 and IRR = 1.02, 95% CI: 1.01 to 1.03, p < .01, respectively). The zero inflated component of the ZINB model yielded shorter distance to Kenya or DRC border, higher incidence rate in the neighboring districts, and higher annual rainfall in the district were associated with the risk of having cholera in the district.</p><p>Conclusions/significance</p><p>The study identified cholera hotspots during the period 2011–2016. The people located near the international borders, internationally shared lakes and river Nile were at higher risk for cholera outbreaks than elsewhere in the country. Targeting cholera interventions to these locations could prevent and ultimately eliminate cholera in Uganda.</p></div

Descriptive statistics of the study variables by district (n = 112).

<p>Descriptive statistics of the study variables by district (n = 112).</p

High risk districts (Hotspots) for Cholera in Uganda, 2011–2016.

<p>High risk districts (Hotspots) for Cholera in Uganda, 2011–2016.</p

Month-wise distribution of the cholera cases and rainfall (mm) by year and by region (eastern vs. western) in Uganda, 2011–2015.

<p>Rainfall data of 2016 were not available, thus the graph of the year was not created.</p

Spatial distribution of cumulative cholera incidence rates across six years (2011–2016) in Uganda.No. inside the district boundary states no. years of cholera occurrence during the study period.

<p>Spatial distribution of cumulative cholera incidence rates across six years (2011–2016) in Uganda.No. inside the district boundary states no. years of cholera occurrence during the study period.</p

Distribution of cholera cases by year, 2011–2016, Uganda. No. of affected districts are shown on the top of bar.

<p>Distribution of cholera cases by year, 2011–2016, Uganda. No. of affected districts are shown on the top of bar.</p

Results of the zero-inflated negative binomial model in a multivariable analysis.

<p>Results of the zero-inflated negative binomial model in a multivariable analysis.</p