ABSTRACT
BACKGROUND: On 20 September 2022, Uganda declared its fifth Sudan virus disease (SVD) outbreak, culminating in 142 confirmed and 22 probable cases. The reproductive rate (R) of this outbreak was 1.25. We described persons who were exposed to the virus, became infected, and they led to the infection of an unusually high number of cases during the outbreak. METHODS: In this descriptive cross-sectional study, we defined a super-spreader person (SSP) as any person with real-time polymerase chain reaction (RT-PCR) confirmed SVD linked to the infection of ≥ 13 other persons (10-fold the outbreak R). We reviewed illness narratives for SSPs collected through interviews. Whole-genome sequencing was used to support epidemiologic linkages between cases. RESULTS: Two SSPs (Patient A, a 33-year-old male, and Patient B, a 26-year-old male) were identified, and linked to the infection of one probable and 50 confirmed secondary cases. Both SSPs lived in the same parish and were likely infected by a single ill healthcare worker in early October while receiving healthcare. Both sought treatment at multiple health facilities, but neither was ever isolated at an Ebola Treatment Unit (ETU). In total, 18 secondary cases (17 confirmed, one probable), including three deaths (17%), were linked to Patient A; 33 secondary cases (all confirmed), including 14 (42%) deaths, were linked to Patient B. Secondary cases linked to Patient A included family members, neighbours, and contacts at health facilities, including healthcare workers. Those linked to Patient B included healthcare workers, friends, and family members who interacted with him throughout his illness, prayed over him while he was nearing death, or exhumed his body. Intensive community engagement and awareness-building were initiated based on narratives collected about patients A and B; 49 (96%) of the secondary cases were isolated in an ETU, a median of three days after onset. Only nine tertiary cases were linked to the 51 secondary cases. Sequencing suggested plausible direct transmission from the SSPs to 37 of 39 secondary cases with sequence data. CONCLUSION: Extended time in the community while ill, social interactions, cross-district travel for treatment, and religious practices contributed to SVD super-spreading. Intensive community engagement and awareness may have reduced the number of tertiary infections. Intensive follow-up of contacts of case-patients may help reduce the impact of super-spreading events.
Subject(s)
Disease Outbreaks , Humans , Uganda/epidemiology , Male , Cross-Sectional Studies , Adult , Female , Hemorrhagic Fever, Ebola/epidemiology , Hemorrhagic Fever, Ebola/virology , Whole Genome Sequencing , Ebolavirus/genetics , Ebolavirus/isolation & purificationABSTRACT
BACKGROUND: In 2022, an Ebola disease outbreak caused by Sudan virus (SUDV) occurred in Uganda, primarily affecting Mubende and Kassanda districts. We determined risk factors for SUDV infection among household members (HHM) of cases. METHODS: We conducted a case-control and retrospective cohort study in January 2023. Cases were RT-PCR-confirmed SUDV infection in residents of Mubende or Kassanda districts during the outbreak. Case-households housed a symptomatic, primary case-patient for ≥ 24 h and had ≥ 1 secondary case-patient with onset < 2 weeks after their last exposure to the primary case-patient. Control households housed a case-patient and other HHM but no secondary cases. A risk factor questionnaire was administered to the primary case-patient or another adult who lived at home while the primary case-patient was ill. We conducted a retrospective cohort study among case-household members and categorized their interactions with primary case-patients during their illnesses as none, minimal, indirect, and direct contact. We conducted logistic regression to explore associations between exposures and case-household status, and Poisson regression to identify risk factors for SUDV infection among HHM. RESULTS: Case- and control-households had similar median sizes. Among 19 case-households and 51 control households, primary case-patient death (adjusted odds ratio [ORadj] = 7.6, 95% CI 1.4-41) and ≥ 2 household bedrooms (ORadj=0.19, 95% CI 0.056-0.71) were associated with case-household status. In the cohort of 76 case-HHM, 44 (58%) were tested for SUDV < 2 weeks from their last contact with the primary case-patient; 29 (38%) were positive. Being aged ≥ 18 years (adjusted risk ratio [aRRadj] = 1.9, 95%CI: 1.01-3.7) and having direct or indirect contact with the primary case-patient (aRRadj=3.2, 95%CI: 1.1-9.7) compared to minimal or no contact increased risk of Sudan virus disease (SVD). Access to a handwashing facility decreased risk (aRRadj=0.52, 95%CI: 0.31-0.88). CONCLUSION: Direct contact, particularly providing nursing care for and sharing sleeping space with SVD patients, increased infection risk among HHM. Risk assessments during contact tracing may provide evidence to justify closer monitoring of some HHM. Health messaging should highlight the risk of sharing sleeping spaces and providing nursing care for persons with Ebola disease symptoms and emphasize hand hygiene to aid early case identification and reduce transmission.
Subject(s)
Disease Outbreaks , Family Characteristics , Hemorrhagic Fever, Ebola , Humans , Uganda/epidemiology , Hemorrhagic Fever, Ebola/epidemiology , Hemorrhagic Fever, Ebola/transmission , Risk Factors , Male , Adult , Female , Retrospective Studies , Case-Control Studies , Adolescent , Young Adult , Middle Aged , Child , Child, Preschool , Ebolavirus , InfantABSTRACT
BACKGROUND: Uganda conducted its third mass long-lasting insecticidal net (LLIN) distribution campaign in 2021. The target of the campaign was to ensure that 100% of households own at least one LLIN per two persons and to achieve 85% use of distributed LLINs. LLIN ownership, use and associated factors were assessed 3 months after the campaign. METHODS: A cross-sectional household survey was conducted in 14 districts from 13 to 30 April, 2021. Households were selected using multistage sampling. Each was asked about LLIN ownership, use, duration since received to the time of interview, and the presence of LLINs was visually verified. Outcomes were having at least one LLIN per two household members, and individual LLIN use. Modified Poisson regression was used to assess associations between exposures and outcomes. RESULTS: In total, 5529 households with 27,585 residents and 15,426 LLINs were included in the analysis. Overall, 95% of households owned ≥ 1 LLIN, 92% of the households owned ≥ 1 LLIN < 3 months old, 64% of households owned ≥ 1 LLIN per two persons in the household. Eighty-seven per cent could sleep under an LLIN if every LLIN in the household were used by two people, but only 69% slept under an LLIN the night before the survey. Factors associated with LLIN ownership included believing that LLINs are protective against malaria (aPR = 1.13; 95% CI 1.04-1.24). Reported use of mosquito repellents was negatively associated with ownership of LLINs (aPR = 0.96; 95% CI 0.95-0.98). The prevalence of LLIN use was 9% higher among persons who had LLINs 3-12 months old (aPR = 1.09; 95% CI 1.06-1.11) and 10% higher among those who had LLINs 13-24 months old (aPR = 1.10; 95% CI 1.06-1.14) than those who had LLINs < 3 months old. Of 3,859 LLINs identified in the households but not used for sleeping the previous night, 3250 (84%) were < 3 months old. Among these 3250, 41% were not used because owners were using old LLINs; 16% were not used because of lack of space for hanging them; 11% were not used because of fear of chemicals in the net; 5% were not used because of dislike of the smell of the nets; and, 27% were not used for other reasons. CONCLUSION: The substantial difference between the population that had access to LLINs and the population that slept under LLINs indicates that the National Malaria Control Programme (NMCP) may need to focus on addressing the main drivers or barriers to LLIN use. NMCP and/or other stakeholders could consider designing and conducting targeted behaviour change communication during subsequent mass distribution of LLINs after the mass distribution campaign to counter misconceptions about new LLINs.