Journal Article > Meta-AnalysisFull Text
Epidemics. 2019 March 2; Volume 27; DOI:10.1016/j.epidem.2019.03.001
Robert A, Camacho A, Edmunds WJ, Baguelin M, Muyembe JJT, et al.
Epidemics. 2019 March 2; Volume 27; DOI:10.1016/j.epidem.2019.03.001
Health care workers (HCW) are at risk of infection during Ebola virus disease outbreaks and therefore may be targeted for vaccination before or during outbreaks. The effect of these strategies depends on the role of HCW in transmission which is understudied. To evaluate the effect of HCW-targeted or community vaccination strategies, we used a transmission model to explore the relative contribution of HCW and the community to transmission. We calibrated the model to data from multiple Ebola outbreaks. We quantified the impact of ahead-of-time HCW-targeted strategies, and reactive HCW and community vaccination. We found that for some outbreaks (we call "type 1″) HCW amplified transmission both to other HCW and the community, and in these outbreaks prophylactic vaccination of HCW decreased outbreak size. Reactive vaccination strategies had little effect because type 1 outbreaks ended quickly. However, in outbreaks with longer time courses ("type 2 outbreaks"), reactive community vaccination decreased the number of cases, with or without prophylactic HCW-targeted vaccination. For both outbreak types, we found that ahead-of-time HCW-targeted strategies had an impact at coverage of 30%. The vaccine strategies tested had a different impact depending on the transmission dynamics and previous control measures. Although we will not know the characteristics of a new outbreak, ahead-of-time HCW-targeted vaccination can decrease the total outbreak size, even at low vaccine coverage.
Journal Article > ResearchFull Text
Epidemics. 2018 December 1; Volume 25; 72-79.; DOI:10.1016/j.epidem.2018.05.008
le Polain de Waroux O, Flasche S, Kucharski AJ, Langendorf C, Ndazima D, et al.
Epidemics. 2018 December 1; Volume 25; 72-79.; DOI:10.1016/j.epidem.2018.05.008
Although patterns of social contacts are believed to be an important determinant of infectious disease transmission, it remains unclear how the frequency and nature of human interactions shape an individual's risk of infection. We analysed data on daily social encounters individually matched to data on S. pneumoniae carriage and acute respiratory symptoms (ARS), from 566 individuals who took part in a survey in South-West Uganda. We found that the frequency of physical (i.e. skin-to-skin), long (≥1 h) and household contacts - which capture some measure of close (i.e. relatively intimate) contact - was higher among pneumococcal carriers than non-carriers, and among people with ARS compared to those without, irrespective of their age. With each additional physical encounter the age-adjusted risk of carriage and ARS increased by 6% (95%CI 2-9%) and 7% (2-13%) respectively. In contrast, the number of casual contacts (<5 min long) was not associated with either pneumococcal carriage or ARS. A detailed analysis by age of contacts showed that the number of close contacts with young children (<5 years) was particularly higher among older children and adult carriers than non-carriers, while the higher number of contacts among people suffering from ARS was more homogeneous across contacts of all ages. Our findings provide key evidence that the frequency of close interpersonal contact is important for transmission of respiratory infections, but not that of casual contacts. Those results are essential for both improving disease prevention and control efforts as well as informing research on infectious disease dynamics and transmission models, and more studies should be undertaken to further validate our results.
Journal Article > ResearchFull Text
Epidemics. 2015 September 3; Volume 14; 1-10.; DOI:10.1016/j.epidem.2015.08.001
Allan M, Grandesso F, Pierre R, Magloire R, Coldiron ME, et al.
Epidemics. 2015 September 3; Volume 14; 1-10.; DOI:10.1016/j.epidem.2015.08.001
BACKGROUND
Cholera is caused by Vibrio cholerae, and is transmitted through fecal-oral contact. Infection occurs after the ingestion of the bacteria and is usually asymptomatic. In a minority of cases, it causes acute diarrhea and vomiting, which can lead to potentially fatal severe dehydration, especially in the absence of appropriate medical care. Immunity occurs after infection and typically lasts 6-36 months. Cholera is responsible for outbreaks in many African and Asian developing countries, and caused localised and episodic epidemics in South America until the early 1990s. Haiti, despite its low socioeconomic status and poor sanitation, had never reported cholera before the recent outbreak that started in October 2010, with over 720,000 cases and over 8700 deaths (Case fatality rate: 1.2%) through 8 December 2014. So far, this outbreak has seen 3 epidemic peaks, and it is expected that cholera will remain in Haiti for some time.
METHODOLOGY/FINDINGS
To trace the path of the early epidemic and to identify hot spots and potential transmission hubs during peaks, we examined the spatial distribution of cholera patients during the first two peaks in Artibonite, the second-most populous department of Haiti. We extracted the geographic origin of 84,000 patients treated in local health facilities between October 2010 and December 2011 and mapped these addresses to 63 rural communal sections and 9 urban cities. Spatial and cluster analysis showed that during the first peak, cholera spread along the Artibonite River and the main roads, and sub-communal attack rates ranged from 0.1% to 10.7%. During the second peak, remote mountain areas were most affected, although sometimes to very different degrees even in closely neighboring locations. Sub-communal attack rates during the second peak ranged from 0.2% to 13.7%. The relative risks at the sub-communal level during the second phase showed an inverse pattern compared to the first phase.
CONCLUSION/SIGNIFICANCE
These findings demonstrate the value of high-resolution mapping for pinpointing locations most affected by cholera, and in the future could help prioritize the places in need of interventions such as improvement of sanitation and vaccination. The findings also describe spatio-temporal transmission patterns of the epidemic in a cholera-naïve country such as Haiti. By identifying transmission hubs, it is possible to target prevention strategies that, over time, could reduce transmission of the disease and eventually eliminate cholera in Haiti.
Cholera is caused by Vibrio cholerae, and is transmitted through fecal-oral contact. Infection occurs after the ingestion of the bacteria and is usually asymptomatic. In a minority of cases, it causes acute diarrhea and vomiting, which can lead to potentially fatal severe dehydration, especially in the absence of appropriate medical care. Immunity occurs after infection and typically lasts 6-36 months. Cholera is responsible for outbreaks in many African and Asian developing countries, and caused localised and episodic epidemics in South America until the early 1990s. Haiti, despite its low socioeconomic status and poor sanitation, had never reported cholera before the recent outbreak that started in October 2010, with over 720,000 cases and over 8700 deaths (Case fatality rate: 1.2%) through 8 December 2014. So far, this outbreak has seen 3 epidemic peaks, and it is expected that cholera will remain in Haiti for some time.
METHODOLOGY/FINDINGS
To trace the path of the early epidemic and to identify hot spots and potential transmission hubs during peaks, we examined the spatial distribution of cholera patients during the first two peaks in Artibonite, the second-most populous department of Haiti. We extracted the geographic origin of 84,000 patients treated in local health facilities between October 2010 and December 2011 and mapped these addresses to 63 rural communal sections and 9 urban cities. Spatial and cluster analysis showed that during the first peak, cholera spread along the Artibonite River and the main roads, and sub-communal attack rates ranged from 0.1% to 10.7%. During the second peak, remote mountain areas were most affected, although sometimes to very different degrees even in closely neighboring locations. Sub-communal attack rates during the second peak ranged from 0.2% to 13.7%. The relative risks at the sub-communal level during the second phase showed an inverse pattern compared to the first phase.
CONCLUSION/SIGNIFICANCE
These findings demonstrate the value of high-resolution mapping for pinpointing locations most affected by cholera, and in the future could help prioritize the places in need of interventions such as improvement of sanitation and vaccination. The findings also describe spatio-temporal transmission patterns of the epidemic in a cholera-naïve country such as Haiti. By identifying transmission hubs, it is possible to target prevention strategies that, over time, could reduce transmission of the disease and eventually eliminate cholera in Haiti.