Conference Material > Video (talk)
Camacho A
Epicentre Scientific Day Paris 2018. 2018 June 7
Other > Pre-Print
bioRxiv. 2017 August 18; DOI:10.1101/177451
Funk S, Camacho A, Kucharski AJ, Lowe R, Eggo RM, et al.
bioRxiv. 2017 August 18; DOI:10.1101/177451
Real-time forecasts based on mathematical models can inform critical decision-making during infectious disease outbreaks. Yet, epidemic forecasts are rarely evaluated during or after the event, and there is little guidance on the best metrics for assessment. Here, we propose an evaluation approach that disentangles different components of forecasting ability using metrics that separately assess the calibration, sharpness and unbiasedness of forecasts. This makes it possible to assess not just how close a forecast was to reality but also how well uncertainty has been quantified. We used this approach to analyse the performance of weekly forecasts we generated in real time in Western Area, Sierra Leone, during the 2013–16 Ebola epidemic in West Africa. We investigated a range of forecast model variants based on the model fits generated at the time with a semi-mechanistic model, and found that good probabilistic calibration was achievable at short time horizons of one or two weeks ahead but models were increasingly inaccurate at longer forecasting horizons. This suggests that forecasts may have been of good enough quality to inform decision making requiring predictions a few weeks ahead of time but not longer, reflecting the high level of uncertainty in the processes driving the trajectory of the epidemic. Comparing forecasts based on the semi-mechanistic model to simpler null models showed that the best semi-mechanistic model variant performed better than the null models with respect to probabilistic calibration, and that this would have been identified from the earliest stages of the outbreak. As forecasts become a routine part of the toolkit in public health, standards for evaluation of performance will be important for assessing quality and improving credibility of mathematical models, and for elucidating difficulties and trade-offs when aiming to make the most useful and reliable forecasts.
Journal Article > ProtocolFull Text
PLOS One. 2023 March 30; Volume 18 (Issue 3); e0283643.; DOI:10.1371/journal.pone.0283643
Penfold S, Adegnika AA, Asogun D, Ayodeji O, Azuogu BN, et al.
PLOS One. 2023 March 30; Volume 18 (Issue 3); e0283643.; DOI:10.1371/journal.pone.0283643
BACKGROUND
Lassa fever (LF), a haemorrhagic illness caused by the Lassa fever virus (LASV), is endemic in West Africa and causes 5000 fatalities every year. The true prevalence and incidence rates of LF are unknown as infections are often asymptomatic, clinical presentations are varied, and surveillance systems are not robust. The aim of the Enable Lassa research programme is to estimate the incidences of LASV infection and LF disease in five West African countries. The core protocol described here harmonises key study components, such as eligibility criteria, case definitions, outcome measures, and laboratory tests, which will maximise the comparability of data for between-country analyses.
METHOD
We are conducting a prospective cohort study in Benin, Guinea, Liberia, Nigeria (three sites), and Sierra Leone from 2020 to 2023, with 24 months of follow-up. Each site will assess the incidence of LASV infection, LF disease, or both. When both incidences are assessed the LASV cohort (n min = 1000 per site) will be drawn from the LF cohort (n min = 5000 per site). During recruitment participants will complete questionnaires on household composition, socioeconomic status, demographic characteristics, and LF history, and blood samples will be collected to determine IgG LASV serostatus. LF disease cohort participants will be contacted biweekly to identify acute febrile cases, from whom blood samples will be drawn to test for active LASV infection using RT-PCR. Symptom and treatment data will be abstracted from medical records of LF cases. LF survivors will be followed up after four months to assess sequelae, specifically sensorineural hearing loss. LASV infection cohort participants will be asked for a blood sample every six months to assess LASV serostatus (IgG and IgM).
DISCUSSION
Data on LASV infection and LF disease incidence in West Africa from this research programme will determine the feasibility of future Phase IIb or III clinical trials for LF vaccine candidates.
Lassa fever (LF), a haemorrhagic illness caused by the Lassa fever virus (LASV), is endemic in West Africa and causes 5000 fatalities every year. The true prevalence and incidence rates of LF are unknown as infections are often asymptomatic, clinical presentations are varied, and surveillance systems are not robust. The aim of the Enable Lassa research programme is to estimate the incidences of LASV infection and LF disease in five West African countries. The core protocol described here harmonises key study components, such as eligibility criteria, case definitions, outcome measures, and laboratory tests, which will maximise the comparability of data for between-country analyses.
METHOD
We are conducting a prospective cohort study in Benin, Guinea, Liberia, Nigeria (three sites), and Sierra Leone from 2020 to 2023, with 24 months of follow-up. Each site will assess the incidence of LASV infection, LF disease, or both. When both incidences are assessed the LASV cohort (n min = 1000 per site) will be drawn from the LF cohort (n min = 5000 per site). During recruitment participants will complete questionnaires on household composition, socioeconomic status, demographic characteristics, and LF history, and blood samples will be collected to determine IgG LASV serostatus. LF disease cohort participants will be contacted biweekly to identify acute febrile cases, from whom blood samples will be drawn to test for active LASV infection using RT-PCR. Symptom and treatment data will be abstracted from medical records of LF cases. LF survivors will be followed up after four months to assess sequelae, specifically sensorineural hearing loss. LASV infection cohort participants will be asked for a blood sample every six months to assess LASV serostatus (IgG and IgM).
DISCUSSION
Data on LASV infection and LF disease incidence in West Africa from this research programme will determine the feasibility of future Phase IIb or III clinical trials for LF vaccine candidates.
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.
Conference Material > Video (talk)
Camacho A
Epicentre Scientific Day Paris 2021. 2021 June 10
Conference Material > Abstract
Camacho A
Epicentre Scientific Day Paris 2018. 2018 June 7
We modelled the plausible drivers of cholera transmission during the course of the outbreak in Yemen. We found a strong association between rainfall and the massive surge of cholera cases in May 2017.
BACKGROUND
In war-torn Yemen, reports of confirmed cholera started in late September 2016. Cholera continues to plague Yemen today in what has become the largest documented cholera epidemic of modern times. We aim to describe key epidemiological features of this epidemic, including the drivers that triggered the massive surge of cholera cases in May 2017.
METHODS
The Health Authorities of Yemen set up a national cholera surveillance system to collect information on suspected cholera cases presenting at health-facilities and MSF cholera treatment centres. We first conducted descriptive analyses at national and governorate levels. We reconstructed the changes in cholera transmission over time by estimating the instantaneous reproduction number, Rt. Finally, we estimated the association between rainfall and the daily cholera incidence during the increasing phase of the second epidemic wave, from April 15 to June 24 2017, by fitting a spatiotemporal regression model.
RESULTS
From 28 September 2016 to 12 March 2018, 1,103,683 suspected cholera cases (attack rate 3.69%) and 2,385 deaths (case fatality risk 0.22%) were reported countrywide. The epidemic comprised of two distinct waves with a surge in transmission in May 2017, corresponding to a median Rt > 2 in 13 of 23 Governorates. Microbiological analyses suggested that the same V. cholerae O1 Ogawa strain circulated in both waves. We found a positive, non-linear, association between the weekly rainfall and cholera incidence in the following 10 days, with weekly rainfall of 25 mm being associated with a 1.42-fold (95% CI: [1.31 – 1.55]) increase in cholera risk compared to a week without rain.
CONCLUSION
Our analysis suggests that the small first cholera epidemic wave seeded cholera across Yemen during the dry season. When the rains returned in April 2017, they triggered widespread cholera transmission that led to the large second wave.
BACKGROUND
In war-torn Yemen, reports of confirmed cholera started in late September 2016. Cholera continues to plague Yemen today in what has become the largest documented cholera epidemic of modern times. We aim to describe key epidemiological features of this epidemic, including the drivers that triggered the massive surge of cholera cases in May 2017.
METHODS
The Health Authorities of Yemen set up a national cholera surveillance system to collect information on suspected cholera cases presenting at health-facilities and MSF cholera treatment centres. We first conducted descriptive analyses at national and governorate levels. We reconstructed the changes in cholera transmission over time by estimating the instantaneous reproduction number, Rt. Finally, we estimated the association between rainfall and the daily cholera incidence during the increasing phase of the second epidemic wave, from April 15 to June 24 2017, by fitting a spatiotemporal regression model.
RESULTS
From 28 September 2016 to 12 March 2018, 1,103,683 suspected cholera cases (attack rate 3.69%) and 2,385 deaths (case fatality risk 0.22%) were reported countrywide. The epidemic comprised of two distinct waves with a surge in transmission in May 2017, corresponding to a median Rt > 2 in 13 of 23 Governorates. Microbiological analyses suggested that the same V. cholerae O1 Ogawa strain circulated in both waves. We found a positive, non-linear, association between the weekly rainfall and cholera incidence in the following 10 days, with weekly rainfall of 25 mm being associated with a 1.42-fold (95% CI: [1.31 – 1.55]) increase in cholera risk compared to a week without rain.
CONCLUSION
Our analysis suggests that the small first cholera epidemic wave seeded cholera across Yemen during the dry season. When the rains returned in April 2017, they triggered widespread cholera transmission that led to the large second wave.
Journal Article > ResearchFull Text
Lancet Global Health. 2018 May 3; Volume 6 (Issue 6); DOI:10.1016/S2214-109X(18)30230-4
Camacho A, Bouhenia M, Alyusfi R, Alkohlani A, Naji MAM, et al.
Lancet Global Health. 2018 May 3; Volume 6 (Issue 6); DOI:10.1016/S2214-109X(18)30230-4
In war-torn Yemen, reports of confirmed cholera started in late September, 2016. The disease continues to plague Yemen today in what has become the largest documented cholera epidemic of modern times. We aimed to describe the key epidemiological features of this epidemic, including the drivers of cholera transmission during the outbreak.
Conference Material > Abstract
Camacho A
Epicentre Scientific Day Paris 2023. 2023 June 8
BACKGROUND
Lassa fever (LF), a haemorrhagic illness caused by the Lassa fever virus (LASV), is endemic in West Africa causing an estimated 300 000 to 500 000 cases and 5 000 fatalities every year. Due to its pandemic potential, LF has been placed on the WHO's list of priority pathogens in order to speed up the development of a safe and effective vaccine. However, the design of successful vaccine trials depends on the true prevalence and incidence rates of LF, which are unknown as infections are often asymptomatic and clinical presentations are varied. The aim of the Enable Lassa research programme is to estimate the incidences of LASV infection and LF disease in five West African countries.
METHODS
We conducted a prospective cohort study in Benin, Guinea, Liberia, Nigeria (three sites), and Sierra Leone from 2020 to 2023, with 24 months of follow-up. Each site assessed the incidence of LASV infection, LF disease, or both. When both incidences are assessed the LASV cohort (n = 1 000 per site) was drawn from the LF cohort (n = 5 000 per site). During recruitment participants completed questionnaires on household composition, socioeconomic status, demographic characteristics, and LF history, and blood samples were collected to determine IgG LASV serostatus. LF disease cohort participants were contacted biweekly to identify acute febrile cases, from whom blood samples were drawn to test for active LASV infection using RT-PCR. LASV infection cohort participants were asked for a blood sample every six months to assess LASV IgG serostatus.
RESULTS
Interim results were obtained in October 2022 using partial data. We focus here on the Nigeria-Edo cohort with a follow-up period of 22 months and 3 serological time-points available (T0, T6, T12). We found a baseline seroprevalence of 43% (95% CI: 42% - 45%), an incidence rate of LASV infection of 13% (10% - 16%) and an incidence rate of LF disease of 0.2% (0.1% - 0.3%). These results suggest that LASV infection is common, but LF disease is rare in hotspot communities. Furthermore, our results suggest that pre-exposure to LASV may temporarily reduce the risk of LF disease. Finally, we found evidence that children may be at greater risk of LF disease than adults due to lower pre-exposure.
CONCLUSION
This is the first epidemiological study to measure the incidence of LF disease and LASV infection in West Africa. The estimates will serve as a basis for the design of future vaccine efficacy trials. The interim results, although limited due to partial data, already suggest that a large sample of several tens of thousands of participants will be required and that children should be included, provided that the candidate vaccine is safe and immunogenic in this group.
KEY MESSAGE
Incidence of Lassa fever is needed to inform vaccine trials. Preliminary results show frequent infections but rare disease, suggesting the need for large vaccine trials.
This abstract is not to be quoted for publication.
Lassa fever (LF), a haemorrhagic illness caused by the Lassa fever virus (LASV), is endemic in West Africa causing an estimated 300 000 to 500 000 cases and 5 000 fatalities every year. Due to its pandemic potential, LF has been placed on the WHO's list of priority pathogens in order to speed up the development of a safe and effective vaccine. However, the design of successful vaccine trials depends on the true prevalence and incidence rates of LF, which are unknown as infections are often asymptomatic and clinical presentations are varied. The aim of the Enable Lassa research programme is to estimate the incidences of LASV infection and LF disease in five West African countries.
METHODS
We conducted a prospective cohort study in Benin, Guinea, Liberia, Nigeria (three sites), and Sierra Leone from 2020 to 2023, with 24 months of follow-up. Each site assessed the incidence of LASV infection, LF disease, or both. When both incidences are assessed the LASV cohort (n = 1 000 per site) was drawn from the LF cohort (n = 5 000 per site). During recruitment participants completed questionnaires on household composition, socioeconomic status, demographic characteristics, and LF history, and blood samples were collected to determine IgG LASV serostatus. LF disease cohort participants were contacted biweekly to identify acute febrile cases, from whom blood samples were drawn to test for active LASV infection using RT-PCR. LASV infection cohort participants were asked for a blood sample every six months to assess LASV IgG serostatus.
RESULTS
Interim results were obtained in October 2022 using partial data. We focus here on the Nigeria-Edo cohort with a follow-up period of 22 months and 3 serological time-points available (T0, T6, T12). We found a baseline seroprevalence of 43% (95% CI: 42% - 45%), an incidence rate of LASV infection of 13% (10% - 16%) and an incidence rate of LF disease of 0.2% (0.1% - 0.3%). These results suggest that LASV infection is common, but LF disease is rare in hotspot communities. Furthermore, our results suggest that pre-exposure to LASV may temporarily reduce the risk of LF disease. Finally, we found evidence that children may be at greater risk of LF disease than adults due to lower pre-exposure.
CONCLUSION
This is the first epidemiological study to measure the incidence of LF disease and LASV infection in West Africa. The estimates will serve as a basis for the design of future vaccine efficacy trials. The interim results, although limited due to partial data, already suggest that a large sample of several tens of thousands of participants will be required and that children should be included, provided that the candidate vaccine is safe and immunogenic in this group.
KEY MESSAGE
Incidence of Lassa fever is needed to inform vaccine trials. Preliminary results show frequent infections but rare disease, suggesting the need for large vaccine trials.
This abstract is not to be quoted for publication.
Journal Article > LetterFull Text
Lancet Global Health. 2018 October 10; Volume 6 (Issue 12); DOI:10.1016/S2214-109X(18)30395-4
Camacho A, Bouhenia M, Azman AS, Poncin M, Zagaria N, et al.
Lancet Global Health. 2018 October 10; Volume 6 (Issue 12); DOI:10.1016/S2214-109X(18)30395-4
Journal Article > ResearchFull Text
PLoS Negl Trop Dis. 2017 July 21; Volume 11 (Issue 7); DOI:10.1371/journal.pntd.0005767
Métras R, Fournié G, Dommerques L, Camacho A, Cavalerie L, et al.
PLoS Negl Trop Dis. 2017 July 21; Volume 11 (Issue 7); DOI:10.1371/journal.pntd.0005767
Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006-2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data.