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BACKGROUND: COVID-19 posed a major threat to countries around the world, but many nations in sub-Saharan Africa avoided large-scale outbreaks. In Uganda, the government first enacted strict lockdowns but later focused on public health policies like masking and distancing. The government also embarked on an ambitious campaign to deliver a free face mask to all Ugandan citizens (approx. 30 million masks). We test whether mask distribution, and public education and encouragement of mask use by community health volunteers, affected mask behavior. METHODS: We collected data about mask behavior before and after masks were distributed in the Mbale district of Uganda. Trained enumerators directly observed mask wearing in public places and asked about mask use via phone surveys. We compared observed and self-reported mask behavior before and after masks were distributed. We also tested whether training volunteers from randomly selected villages to educate the public about COVID-19 and masks affected behavior, attitudes, and knowledge among mask recipients. RESULTS: We collected 6,381 direct observations of mask use at baseline (February 2021) and 19,855 observations at endline (April 2021). We conducted a listing of 9,410 households eligible for phone surveys and randomly selected 399 individuals (4.2%) at baseline and 640 (6.8%) at endline. Fewer than 1% of individuals were observed wearing masks at baseline: 0.9% were seen with a mask and 0.5% wore masks over mouth and nose. Mask wearing significantly increased at endline but remained low: 1.8% of people were observed with masks and 1.1% were seen wearing masks correctly after the distribution campaign. At the same time, a high proportion of people reported using masks: 63.0% of people reported using masks at baseline and 65.3% at endline when walking around their villages. When respondents were asked about mask use in public places, 94.7% reported using masks at baseline and 97.4% reported using masks at endline. We found no differences in knowledge, behavior, or attitudes among mask recipients in villages where volunteers were tasked with conveying information about COVID-19 and masks during distribution. CONCLUSION: Mask use remained low in Mbale district of Uganda during study observation period even after free masks were distributed. Encouraging new health behaviors may need to involve more intensive interventions that include reminders and address social norms.
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COVID-19 , Masks , Humans , Uganda , COVID-19/prevention & control , COVID-19/epidemiology , Female , Male , Adult , Young Adult , Middle Aged , Adolescent , SARS-CoV-2/isolation & purification , Health Knowledge, Attitudes, Practice , ChildABSTRACT
BACKGROUND: The rVSVΔG-ZEBOV-GP Ebola vaccine (rVSV-ZEBOV) has been used in response to Ebola disease outbreaks caused by Ebola virus (EBOV). Understanding Ebola knowledge, attitudes, and practices (KAP) and the long-term immune response following rVSV-ZEBOV are critical to inform recommendations on future use. METHODS: We administered surveys and collected blood samples from healthcare workers (HCWs) from seven Ugandan healthcare facilities. Questionnaires collected information on demographic characteristics and KAP related to Ebola and vaccination. IgG ELISA, virus neutralization, and interferon gamma ELISpot measured immunological responses against EBOV glycoprotein (GP). RESULTS: Overall, 37 % (210/565) of HCWs reported receiving any Ebola vaccination. Knowledge that rVSV-ZEBOV only protects against EBOV was low among vaccinated (32 %; 62/192) and unvaccinated (7 %; 14/200) HCWs. Most vaccinated (91 %; 192/210) and unvaccinated (92 %; 326/355) HCWs wanted to receive a booster or initial dose of rVSV-ZEBOV, respectively. Median time from rVSV-ZEBOV vaccination to sample collection was 37.7 months (IQR: 30.5, 38.3). IgG antibodies against EBOV GP were detected in 95 % (61/64) of HCWs with vaccination cards and in 84 % (162/194) of HCWs who reported receiving a vaccination. Geometric mean titer among seropositive vaccinees was 0.066 IU/mL (95 % CI: 0.058-0.076). CONCLUSION: As Uganda has experienced outbreaks of Sudan virus and Bundibugyo virus, for which rVSV-ZEBOV does not protect against, our findings underscore the importance of continued education and risk communication to HCWs on Ebola and other viral hemorrhagic fevers. IgG antibodies against EBOV GP were detected in most vaccinated HCWs in Uganda 2â4 years after vaccination; however, the duration and correlates of protection warrant further investigation.
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BACKGROUND: Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterising recent RVF disease events in East Africa. METHODS: Data on 100 disease events (2008-2022) from Kenya, Uganda and Tanzania were obtained from public databases and institutions, and modelled against possible geoecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalised difference vegetation index (NDVI), livestock production system, land-use change and long-term climatic variations. Decadal climatic variations between 1980 and 2022 were evaluated for association with the changing disease pattern. RESULTS: Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1-3) and three livestock cases (IQR, 2-7). These clusters exhibited minimal human mortality (IQR, 0-1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geoecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1°C increase in temperature and a 1-unit increase in NDVI, one months prior were associated with increased RVF incidence rate ratios of 1.20 (95% CI 1.1, 1.2) and 1.93 (95% CI 1.01, 3.71), respectively. Long-term climatic trends showed a significant decadal increase in annual mean temperature (0.12-0.3°C/decade, p<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (p<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively. CONCLUSION: These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics.
Subject(s)
Climate Change , Rift Valley Fever , Rift Valley Fever/epidemiology , Humans , Animals , Africa, Eastern/epidemiology , Livestock , Risk Factors , Uganda/epidemiology , Cluster Analysis , Disease Outbreaks , Kenya/epidemiologyABSTRACT
Background: Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterizing recent RVF disease events in East Africa. Methods: Data on 100 disease events (2008 - 2022) from Kenya, Uganda, and Tanzania were obtained from public databases and institutions, and modeled against possible geo-ecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalized difference vegetation index (NDVI), livestock production system, land-use change, and long-term climatic variations. Decadal climatic variations between 1980-2022 were evaluated for association with the changing disease pattern. Results: Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1-3) and 3 livestock cases (IQR, 2-7). These clusters exhibited minimal human mortality (IQR 0-1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geo-ecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1oC increase in temperature and 1-unit increase in NDVI, 1-3 months prior were associated with increased RVF incidence rate ratios (IRR) of 1.20 (95% CI 1.1,1.2) and 9.88 (95% CI 0.85, 119.52), respectively. Long-term climatic trends showed significant decadal increase in annual mean temperature (0.12 to 0.3oC/decade, P<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (P<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively. Conclusion: These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics. Key questions: What is already known on this topic?: Rift Valley fever is recognized for its association with heavy rainfall, flooding, and El Niño rains in the East African region. A growing body of recent studies has highlighted a shifting landscape of the disease, marked by an expanding geographic range and an increasing number of small RVF clusters.What this study adds: This study challenges previous beliefs about RVF, revealing that it predominantly occurs in small clusters rather than large outbreaks, and its association with El Niño is not as pronounced as previously thought. Over 65% of these clusters are concentrated in the highlands of Kenya and Uganda, with 35% occurring in previously unaffected regions, accompanied by an increase in temperature and total rainfall between 1980 and 2022, along with a rise in the annual number of rainy days. Notably, the observed rainfall increases are particularly significant during the short-rains season (October-December), aligning with a secondary peak in RVF incidence. In contrast, the lowlands of East Africa, where typical RVF epidemics occur, display smaller and more varied trends in annual rainfall.How this study might affect research, practice, or policy: The worldwide consequence of the expanding RVF cluster is the broader dispersion of the virus, leading to the establishment of new regions with virus endemicity. This escalation heightens the risk of more extensive extreme-weather-associated RVF epidemics in the future. Global public health institutions must persist in developing preparedness and response strategies for such scenarios. This involves the creation and approval of human RVF vaccines and therapeutics, coupled with a rapid distribution plan through regional banks.
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On 20th September 2022, Uganda declared the 7th outbreak of Ebola virus disease (EVD) caused by the Sudan Ebola strain following the confirmation of a case admitted at Mubende Regional Referral Hospital. Upon confirmation, the Government of Uganda immediately activated the national incident management system to initiate response activities. Additionally, a multi-country emergency stakeholder meeting was held in Kampala; convening Ministers of Health from neighbouring Member States to undertake cross-border preparedness and response actions. The outbreak spanned 69 days and recorded 164 cases (142 confirmed, 22 probable), 87 recoveries and 77 deaths (case fatality ratio of 47%). Nine out of 136 districts were affected with transmission taking place in 5 districts but spilling over in 4 districts without secondary transmission. As part of the response, the Government galvanised robust community mobilisation and initiated assessment of medical counter measures including therapeutics, new diagnostics and vaccines. This paper highlights the response actions that contributed to the containment of this outbreak in addition to the challenges faced with a special focus on key recommendations for better control of future outbreaks.
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BACKGROUND: Despite the discovery of vaccines, the control, and prevention of Coronavirus disease 2019 (COVID-19) relied on non-pharmaceutical interventions (NPIs). This article describes the development and application of the Public Health Act to implement NPIs for COVID-19 pandemic control in Uganda. METHODS: This is a case study of Uganda's experience with enacting COVID-19 Rules under the Public Health Act Cap. 281. The study assessed how and what Rules were developed, their influence on the outbreak progress, and litigation. The data sources reviewed were applicable laws and policies, Presidential speeches, Cabinet resolutions, statutory instruments, COVID-19 situation reports, and the registry of court cases that contributed to a triangulated analysis. RESULTS: Uganda applied four COVID-19 broad Rules for the period March 2020 to October 2021. The Minister of Health enacted the Rules, which response teams, enforcement agencies, and the general population followed. The Presidential speeches, their expiry period and progress of the pandemic curve led to amendment of the Rules twenty one (21) times. The Uganda Peoples Defense Forces Act No. 7 of 2005, the Public Finance Management Act No. 3 of 2015, and the National Policy for Disaster Preparedness and Management supplemented the enacted COVID-19 Rules. However, these Rules attracted specific litigation due to perceived infringement on certain human rights provisions. CONCLUSIONS: Countries can enact supportive legislation within the course of an outbreak. The balance of enforcing public health interventions and human rights infringements is an important consideration in future. We recommend public sensitization about legislative provisions and reforms to guide public health responses in future outbreaks or pandemics.
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COVID-19 , Public Health , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Uganda/epidemiology , Pandemics/prevention & control , Disease OutbreaksABSTRACT
In 2017, the Global Task Force for Cholera Control (GTFCC) set a goal to eliminate cholera from ≥ 20 countries and to reduce cholera deaths by 90% by 2030. Many countries have included oral cholera vaccine (OCV) in their cholera control plans. We felt that a simple, user-friendly monitoring tool would be useful to guide national progress toward cholera elimination. We reviewed cholera surveillance data of Uganda from 2015 to 2021 by date and district. We defined a district as having eliminated cholera if cholera was not reported in that district for at least 4 years. We prepared maps to show districts with cholera, districts that had eliminated it, and districts that had eliminated it but then "relapsed." These maps were compared with districts where OCV was used and the hotspot map recommended by the GTFCC. Between 2018 and 2021, OCV was administered in 16 districts previously identified as hotspots. In 2018, cholera was reported during at least one of the four previous years from 36 of the 146 districts of Uganda. This number decreased to 18 districts by 2021. Cholera was deemed "eliminated" from four of these 18 districts but then "relapsed." The cholera elimination scorecard effectively demonstrated national progress toward cholera elimination and identified districts where additional resources are needed to achieve elimination by 2030. Identification of the districts that have eliminated cholera and those that have relapsed will assist the national programs to focus on addressing the factors that result in elimination or relapse of cholera.
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Cholera Vaccines , Cholera , Humans , Uganda/epidemiology , Cholera/epidemiology , Cholera/prevention & control , Administration, OralABSTRACT
Uganda established a National Action Plan for Health Security in 2019, following a Joint External Evaluation (JEE) of International Health Regulations (2005) capacities in 2017. The action plan enhanced national health security awareness, but implementation efforts were affected by limited funding, excess of activities, and challenges related to monitoring and evaluation. To improve implementation, Uganda conducted a multisectoral health security self-assessment in 2021 using the second edition of the JEE tool and developed a 1-year operational plan. From 2017 to 2021, Uganda's composite ReadyScore improved by 20%, with improvement in 13 of the 19 technical areas. Indicator scores showing limited capacity declined from 30% to 20%, and indicators with no capacity declined from 10% to 2%. More indicators had developed (47% vs 40%), demonstrated (29% vs 20%), and sustained (2% vs 0%) capacities in 2021 compared with 2017. Using the self-assessment JEE scores, 72 specific activities from the International Health Regulations (2005) benchmarks tool were selected for inclusion in a 1-year operational plan (2021-2022). In contrast to the 264 broad activities in the 5-year national action plan, the operational plan prioritized a small number of activities to enable sectors to focus limited resources on implementation. While certain capacities improved before and during implementation of the action plan, countries may benefit from using short-term operational planning to develop realistic and actionable health security plans to improve health security capacities.
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Global Health , Public Health , Humans , Uganda , Self-Assessment , International CooperationABSTRACT
Background: In June 2019, landslides and floods in Bududa district, eastern Uganda, claimed lives and led to a cholera outbreak. The affected communities had inadequate access to clean water and sanitation. Objective: To share the experience of controlling a cholera outbreak in Bududa district, after landslides and floods. Methods: A descriptive cross-sectional study was carried out in which outbreak investigation reports, weekly epidemiological data and disaster response reports were reviewed. Results: On 4 - 5th June 2019, heavy rainfall resulted in four landslides which caused six fatalities, 27 injuries, floods and displaced 480 persons. Two weeks later, a cholera outbreak was confirmed in Bududa district. The Ministry of Health (MoH) rapidly deployed oral cholera vaccine (OCV) from local reserves and mass vaccinated 93% of the target population in 22 affected parishes. The outbreak was controlled in 10 weeks with 67 cholera cases and 1 death reported. However, WaSH conditions remained poor, with only, 24.2 % (879/3,628) of the households with washable latrines, 26.8% (1,023/3,818) had hand-washing facilities with soap and 33.6% (1617/4807) used unsafe water. Conclusion: The OCV stockpile by the MoH helped Uganda to control cholera promptly in Bududa district. High-risk countries should keep OCV reserves for emergencies.
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Cholera Vaccines , Cholera , Disease Outbreaks , Floods , Landslides , Humans , Cholera/epidemiology , Cholera/prevention & control , Uganda/epidemiology , Disease Outbreaks/prevention & control , Cross-Sectional Studies , Cholera Vaccines/administration & dosage , Adult , Male , Female , Adolescent , Young Adult , Sanitation , Child , Middle Aged , Child, Preschool , InfantABSTRACT
The COVID-19 pandemic spread between neighboring countries through land, water, and air travel. Since May 2020, ministries of health for the Democratic Republic of the Congo, Tanzania, and Uganda have sought to clarify population movement patterns to improve their disease surveillance and pandemic response efforts. Ministry of Health-led teams completed focus group discussions with participatory mapping using country-adapted Population Connectivity Across Borders toolkits. They analyzed the qualitative and spatial data to prioritize locations for enhanced COVID-19 surveillance, community outreach, and cross-border collaboration. Each country employed varying toolkit strategies, but all countries applied the results to adapt their national and binational communicable disease response strategies during the pandemic, although the Democratic Republic of the Congo used only the raw data rather than generating datasets and digitized products. This 3-country comparison highlights how governments create preparedness and response strategies adapted to their unique sociocultural and cross-border dynamics to strengthen global health security.
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Air Travel , COVID-19 , Communicable Diseases , Humans , Disease Outbreaks , COVID-19/epidemiology , Pandemics/prevention & control , Communicable Diseases/epidemiology , Democratic Republic of the Congo/epidemiologyABSTRACT
INTRODUCTION: On 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 METHODS: In 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. RESULTS: As 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. CONCLUSION: COVID-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.
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BACKGROUND: Model-based small area estimation methods can help generate parameter estimates at the district level, where planned population survey sample sizes are not large enough to support direct estimates of HIV prevalence with adequate precision. We computed district-level HIV prevalence estimates and their 95% confidence intervals for districts in Uganda. METHODS: Our analysis used direct survey and model-based estimation methods, including Fay-Herriot (area-level) and Battese-Harter-Fuller (unit-level) small area models. We used regression analysis to assess for consistency in estimating HIV prevalence. We use a ratio analysis of the mean square error and the coefficient of variation of the estimates to evaluate precision. The models were applied to Uganda Population-Based HIV Impact Assessment 2016/2017 data with auxiliary information from the 2016 Lot Quality Assurance Sampling survey and antenatal care data from district health information system datasets for unit-level and area-level models, respectively. RESULTS: Estimates from the model-based and the direct survey methods were similar. However, direct survey estimates were unstable compared with the model-based estimates. Area-level model estimates were more stable than unit-level model estimates. The correlation between unit-level and direct survey estimates was (ß1 = 0.66, r2 = 0.862), and correlation between area-level model and direct survey estimates was (ß1 = 0.44, r2 = 0.698). The error associated with the estimates decreased by 37.5% and 33.1% for the unit-level and area-level models, respectively, compared to the direct survey estimates. CONCLUSIONS: Although the unit-level model estimates were less precise than the area-level model estimates, they were highly correlated with the direct survey estimates and had less standard error associated with estimates than the area-level model. Unit-level models provide more accurate and reliable data to support local decision-making when unit-level auxiliary information is available.
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HIV Infections/epidemiology , Adolescent , Adult , Algorithms , Female , Humans , Lot Quality Assurance Sampling , Male , Middle Aged , Pregnancy , Prenatal Care , Prevalence , Uganda/epidemiology , Young AdultABSTRACT
During 2016 to 2019, cholera outbreaks were reported commonly to the Ministry of Health from refugee settlements. To further understand the risks cholera posed to refugees, a review of surveillance data on cholera in Uganda for the period 2016-2019 was carried out. During this 4-year period, there were seven such outbreaks with 1,495 cases and 30 deaths in five refugee settlements and one refugee reception center. Most deaths occurred early in the outbreak, often in the settlements or before arrival at a treatment center rather than after arrival at a treatment center. During the different years, these outbreaks occurred during different times of the year but simultaneously in settlements that were geographically separated and affected all ages and genders. Some outbreaks spread to the local populations within Uganda. Cholera control prevention measures are currently being implemented; however, additional measures are needed to reduce the risk of cholera among refugees including oral cholera vaccination and a water, sanitation and hygiene package during the refugee registration process. A standardized protocol is needed to quickly conduct case-control studies to generate information to guide future cholera outbreak prevention in refugees and the host population.
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Cholera/epidemiology , Disease Outbreaks/prevention & control , Refugees , Adolescent , Adult , Case-Control Studies , Child , Child, Preschool , Cholera/etiology , Cholera/mortality , Cross-Sectional Studies , Disease Outbreaks/statistics & numerical data , Female , Humans , Hygiene/standards , Male , Middle Aged , Risk Factors , Sanitation/standards , Uganda/epidemiology , Young AdultABSTRACT
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.
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Civil Defense/standards , Disease Outbreaks/statistics & numerical data , Hemorrhagic Fever, Ebola/therapy , Civil Defense/methods , Civil Defense/statistics & numerical data , Hemorrhagic Fever, Ebola/epidemiology , Humans , Public Health/methods , Public Health/standards , Uganda/epidemiology , World Health Organization/organization & administrationABSTRACT
Tailoring communicable disease preparedness and response strategies to unique population movement patterns between an outbreak area and neighboring countries can help limit the international spread of disease. Global recognition of the value of addressing community connectivity in preparedness and response, through field work and visualizing the identified movement patterns, is reflected in the World Health Organization's declaration on July 17, 2019, that the 10th Ebola virus disease (Ebola) outbreak in the Democratic Republic of the Congo (DRC) was a Public Health Emergency of International Concern (1). In March 2019, the Infectious Diseases Institute (IDI), Uganda, in collaboration with the Ministry of Health (MOH) Uganda and CDC, had previously identified areas at increased risk for Ebola importation by facilitating community engagement with participatory mapping to characterize cross-border population connectivity patterns. Multisectoral participants identified 31 locations and associated movement pathways with high levels of connectivity to the Ebola outbreak areas. They described a major shift in the movement pattern between Goma (DRC) and Kisoro (Uganda), mainly through Rwanda, when Rwanda closed the Cyanika ground crossing with Uganda. This closure led some travelers to use a potentially less secure route within DRC. District and national leadership used these results to bolster preparedness at identified points of entry and health care facilities and prioritized locations at high risk further into Uganda, especially markets and transportation hubs, for enhanced preparedness. Strategies to forecast, identify, and rapidly respond to the international spread of disease require adapting to complex, dynamic, multisectoral cross-border population movement, which can be influenced by border control and public health measures of neighboring countries.
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Disease Outbreaks , Hemorrhagic Fever, Ebola/epidemiology , Human Migration/statistics & numerical data , Community Participation , Democratic Republic of the Congo/epidemiology , Disease Outbreaks/prevention & control , Hemorrhagic Fever, Ebola/prevention & control , Humans , Rwanda/epidemiology , Uganda/epidemiologyABSTRACT
On August 1, 2018, the Democratic Republic of the Congo (DRC) declared its 10th Ebola virus disease (Ebola) outbreak in an area with a high volume of cross-border population movement to and from neighboring countries. The World Health Organization (WHO) designated Rwanda, South Sudan, and Uganda as the highest priority countries for Ebola preparedness because of the high risk for cross-border spread from DRC (1). Countries might base their disease case definitions on global standards; however, historical context and perceived risk often affect why countries modify and adapt definitions over time, moving toward or away from regional harmonization. Discordance in case definitions among countries might reduce the effectiveness of cross-border initiatives during outbreaks with high risk for regional spread. CDC worked with the ministries of health (MOHs) in DRC, Rwanda, South Sudan, and Uganda to collect MOH-approved Ebola case definitions used during the first 6 months of the outbreak to assess concordance (i.e., commonality in category case definitions) among countries. Changes in MOH-approved Ebola case definitions were analyzed, referencing the WHO standard case definition, and concordance among the four countries for Ebola case categories (i.e., community alert, suspected, probable, confirmed, and case contact) was assessed at three dates (2). The number of country-level revisions ranged from two to four, with all countries revising Ebola definitions by February 2019 after a December 2018 peak in incidence in DRC. Case definition complexity increased over time; all countries included more criteria per category than the WHO standard definition did, except for the "case contact" and "confirmed" categories. Low case definition concordance and lack of awareness of regional differences by national-level health officials could reduce effectiveness of cross-border communication and collaboration. Working toward regional harmonization or considering systematic approaches to addressing country-level differences might increase efficiency in cross-border information sharing.
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Disease Outbreaks , Hemorrhagic Fever, Ebola/diagnosis , Hemorrhagic Fever, Ebola/epidemiology , Public Health Surveillance/methods , Democratic Republic of the Congo/epidemiology , Humans , Rwanda/epidemiology , South Sudan/epidemiology , Time Factors , Uganda/epidemiologyABSTRACT
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.
Subject(s)
Clinical Laboratory Techniques/methods , Communicable Disease Control/methods , Disease Outbreaks , Marburg Virus Disease/epidemiology , Marburg Virus Disease/pathology , Marburgvirus/isolation & purification , Adult , Animals , Cluster Analysis , Disease Transmission, Infectious/prevention & control , Family Health , Female , High-Throughput Nucleotide Sequencing , Humans , Male , Marburg Virus Disease/mortality , Middle Aged , Mortality , Uganda/epidemiology , Virus CultivationABSTRACT
OBJECTIVE: To demonstrate the feasibility of integrated screening for cryptococcal antigenemia and tuberculosis (TB) before antiretroviral therapy (ART) initiation and to assess disease specific and all-cause mortality in the first 6 months of follow-up. METHODS: We enrolled a cohort of HIV-infected, ART-naive adults with CD4 counts ≤250 cells per microliter in rural Uganda who were followed for 6 months after ART initiation. All subjects underwent screening for TB; those with CD4 ≤100 cells per microliter also had cryptococcal antigen (CrAg) screening. For those who screened positive, standard treatment for TB or preemptive treatment for cryptococcal infection was initiated, followed by ART 2 weeks later. RESULTS: Of 540 participants enrolled, pre-ART screening detected 10.6% (57/540) with prevalent TB and 6.8% (12/177 with CD4 count ≤100 cells/µL) with positive serum CrAg. After ART initiation, 13 (2.4%) patients were diagnosed with TB and 1 patient developed cryptococcal meningitis. Overall 7.2% of participants died (incidence rate 15.6 per 100 person-years at risk). Death rates were significantly higher among subjects with TB and cryptococcal antigenemia compared with subjects without these diagnoses. In multivariate analysis, significant risk factors for mortality were male sex, baseline anemia of hemoglobin ≤10 mg/dL, wasting defined as body mass index ≤15.5 kg/m, and opportunistic infections (TB, positive serum CrAg). CONCLUSIONS: Pre-ART screening for opportunistic infections detects many prevalent cases of TB and cryptococcal infection. However, severely immunosuppressed and symptomatic HIV patients continue to experience high mortality after ART initiation.