Chains of transmission and control of Ebola virus disease in Conakry, Guinea, in 2014: an observational study

Abstract

Background: An epidemic of Ebola virus disease of unprecedented size continues in parts of west Africa. For the first time, large urban centres such as Conakry, the capital of Guinea, are affected. We did an observational study of patients with Ebola virus disease in three regions of Guinea, including Conakry, aiming to map the routes of transmission and assess the effect of interventions.

Methods: Between Feb 10, 2014, and Aug 25, 2014, we obtained data from the linelist of all confirmed and probable cases in Guinea (as of Sept 16, 2014), a laboratory database of information about patients, and interviews with patients and their families and neighbours. With this information, we mapped chains of transmission, identified which setting infections most probably originated from (community, hospitals, or funerals), and computed the context-specific and overall reproduction numbers.

Findings: Of 193 confirmed and probable cases of Ebola virus disease reported in Conakry, Boffa, and Télimélé, 152 (79%) were positioned in chains of transmission. Health-care workers contributed little to transmission. In March, 2014, individuals with Ebola virus disease who were not health-care workers infected a mean of 2·3 people (95% CI 1·6-3·2): 1·4 (0·9-2·2) in the community, 0·4 (0·1-0·9) in hospitals, and 0·5 (0·2-1·0) at funerals. After the implementation of infection control in April, the reproduction number in hospitals and at funerals reduced to lower than 0·1. In the community, the reproduction number dropped by 50% for patients that were admitted to hospital, but remained unchanged for those that were not. In March, hospital transmissions constituted 35% (seven of 20) of all transmissions and funeral transmissions constituted 15% (three); but from April to the end of the study period, they constituted only 9% (11 of 128) and 4% (five), respectively. 82% (119 of 145) of transmission occurred in the community and 72% (105) between family members. Our simulations show that a 10% increase in hospital admissions could have reduced the length of chains by 26% (95% CI 4-45).

Interpretation: In Conakry, interventions had the potential to stop the epidemic, but reintroductions of the disease and poor cooperation of a few families led to prolonged low-level spread, showing the challenges of Ebola virus disease control in large urban centres. Monitoring of chains of transmission is crucial to assess and optimise local control strategies for Ebola virus disease.

Funding: Labex IBEID, Reacting, PREDEMICS, NIGMS MIDAS initiative, Institut Pasteur de Dakar.

Figure 1. Epidemiological context

A. Map of Guinea. Conakry, the capital city of Guinea is highlighted along with two prefectures, Telimélé and Boffa, the chains of transmission of Conakry expanded to. The total number of probable and confirmed cases reported from March to August 2014 is also provided. B. Epidemic curve of probable and confirmed EVD cases for Guinea (grey) and for the prefectures of Conakry/Telimélé/Boffa (pink). The number of cases appearing in the chains of transmission of Conakry/Telimélé/Boffa is indicated in red. From the end of March, control measures including the opening of a treatment center, social mobilization among HCW, secured burial by professional staff were implemented.

Figure 2. Transmission tree

A. Proportion of cases infected in the community, at hospital and at funerals. B. Number of cases infected in each context, by month of symptom onset. C. Context-specific and overall reproduction numbers by month of symptom onset. The reproduction number is the mean number of persons infected by a case. D. A fully resolved transmission tree. Each point represents an EVD case. The size of the point is proportional to overall reproduction number R. Dates of symptom onset are indicated in the figure for cases with R≥3. HCWs are represented by squares. The color of the arrow indicates the context of transmission. Cases were stratified by their date of symptom onset.

Figure 3. Impact of interventions

A. Context-specific and overall reproduction numbers for HCW and non-HCW case patients in March, before infection control was implemented. B. Context-specific and overall reproduction numbers for HCW and for non-HCW case patients who were/were not hospitalized from April to August, i.e. after infection control was implemented. C. Estimated reduction in the size of the chain as a function of the proportion of hospitalized cases. D. Estimated reduction in the number of hospitalized cases as a function of the proportion of hospitalized cases. Cases were stratified by their date of symptom onset.