Search

Background RTS,S/AS01 is the first malaria vaccine to be approved and recommended for widespread implementation by the World Health Organization (WHO). Trials reported lower vaccine efficacies in higher-incidence sites, potentially due to a “rebound” in malaria cases in vaccinated children. When naturally acquired protection in the control group rises and vaccine protection in the vaccinated wanes concurrently, malaria incidence can become greater in the vaccinated than in the control group, resulting in negative vaccine efficacies. Methods Using data from the 2009–2014 phase III trial (NCT00866619) in Lilongwe, Malawi; Kintampo, Ghana; and Lambaréné, Gabon, we evaluate this hypothesis by estimating malaria incidence in each vaccine group over time and in varying transmission settings. After estimating transmission intensities using ecological variables, we fit models with 3-way interactions between vaccination, time, and transmission intensity. Results Over time, incidence decreased in the control group and increased in the vaccine group. Three-dose efficacy in the lowest-transmission-intensity group (0.25 cases per person-year [CPPY]) decreased from 88.2% to 15.0% over 4.5 years, compared with 81.6% to −27.7% in the highest-transmission-intensity group (3 CPPY). Conclusions These findings suggest that interventions, including the fourth RTS,S dose, that protect vaccinated individuals during the potential rebound period should be implemented for high-transmission settings.

Malaria programs rely upon a variety of diagnostic assays, including rapid diagnostic tests (RDTs), microscopy, polymerase chain reaction (PCR), and bead-based immunoassays (BBA), to monitor malaria prevalence and support control and elimination efforts. Data comparing these assays are limited, especially from high-burden countries like the Democratic Republic of the Congo (DRC). Using cross-sectional and routine data, we compared diagnostic performance andPlasmodium falciparumprevalence estimates across health areas of varying transmission intensity to illustrate the relevance of assay performance to malaria control programs. Data and samples were collected between March-June 2018 during a cross-sectional household survey across three health areas with low, moderate, and high transmission intensities within two health zones of Kinshasa province, DRC.Samples from 1,431 participants were evaluated using RDT, microscopy, PCR, and BBA.P. falciparumparasite prevalence varied between diagnostic methods across all health areas, with the highest prevalence estimates observed in Bu (57.4-72.4% across assays), followed by Kimpoko (32.6-53.2%), and Voix du Peuple (3.1-8.4%). Using latent class analysis to compare these diagnostic methods against an “alloyed gold standard,” the most sensitive diagnostic method was BBA in Bu (high prevalence) and Voix du Peuple (low prevalence), while PCR diagnosis was most sensitive in Kimpoko (moderate prevalence). RDTs were consistently the most specific diagnostic method in all health areas. Among 9.0 million people residing in Kinshasa Province in 2018, the estimatedP. falciparumprevalence by microscopy, PCR, and BBA were nearly double that of RDT.Comparison of malaria RDT, microscopy, PCR, and BBA results confirmed differences in sensitivity and specificity that varied by endemicity, with PCR and BBA performing best for detecting anyP. falciparuminfection. Prevalence estimates varied widely depending on assay type for parasite detection. Inherent differences in assay performance should be carefully considered when using community survey and surveillance data to guide policy decisions.

Background Health care workers (HCW) are more likely to be exposed to Ebola virus (EBOV) during an outbreak compared to people in the general population due to close physical contact with patients and potential exposure to infectious fluids. However, not all will fall ill. Despite evidence of subclinical and paucisymptomatic Ebola virus disease (EVD), prevalence and associated risk factors remain unknown. Methods We conducted a serosurvey among HCW in Boende, Tshuapa Province, Democratic Republic of Congo. Human anti-EBOV glycoprotein IgG titers were measured using a commercially available ELISA kit. We assessed associations between anti-EBOV IgG seroreactivity, defined as ≥2.5 units/mL, and risk factors using univariable and multivariable logistic regression. Sensitivity analyses explored a more conservative cutoff, >5 units/mL. Results Overall, 22.5% of HCWs were seroreactive for EBOV. In multivariable analyses, using any form of personal protective equipment when interacting with a confirmed, probable, or suspect EVD case was negatively associated with seroreactivity (adjusted odds ratio, 0.23; 95% confidence interval, .07–.73). Discussion Our results suggest high exposure to EBOV among HCWs and provide additional evidence for asymptomatic or minimally symptomatic EVD. Further studies should be conducted to determine the probability of onward transmission and if seroreactivity is associated with immunity.

What is the effect of migration on fuel use in rural Zambia? Opportunities to increase income can be scarce in this setting; in response, households may pursue a migration strategy to increase resources as well as to mitigate risk. Migrant remittances may make it possible for households to shift from primary reliance on firewood to charcoal, and the loss of productive labor through migration may reinforce this shift. This paper uses four waves of panel data collected as part of the Child Grant Programme in rural Zambia to examine the connection between migration and the choice of firewood or charcoal as cooking fuel and finds evidence for both mechanisms. Importantly, this paper considers migration as a process, including out as well as return migration, embedding it in the context of household dynamics generally. Empirical results suggest that while out-migration helps move households away from firewood as a fuel source, return migration moves them back, but because the former is more common, the overall effect of migration is to shift households away from primary reliance on firewood.

Indigenous populations often have poorer health outcomes than the general population. Marginalization, colonization, and migration from traditional lands have all affected traditional medicine usage, health access, and indigenous health equity. An in-depth understanding of health for specific populations is essential to develop actionable insights into contributing factors to poor indigenous health. To develop a more complete, nuanced understanding of indigenous health status, we conducted first-person interviews with both the indigenous Baka and neighboring Bantu villagers (the reference population in the region), as well as local clinicians in Southern Cameroon. These interviews elucidated perspectives on the most pressing challenges to health and assets to health for both groups, including access to health services, causes of illness, the uses and values of traditional versus modern medicine, and community resilience during severe health events. Baka interviewees, in particular, reported facing health challenges due to affordability and discrimination in public health centers, health effects due to migration from their traditional lands, and a lack of culturally appropriate public health services.

Background Our understanding of the different effects of targeted versus nontargeted violence on Ebola virus (EBOV) transmission in Democratic Republic of the Congo (DRC) is limited. Methods We used time-series data of case counts to compare individuals in Ebola-affected health zones in DRC, April 2018–August 2019. Exposure was number of violent events per health zone, categorized into Ebola-targeted or Ebola-untargeted, and into civilian-induced, (para)military/political, or protests. Outcome was estimated daily reproduction number (Rt) by health zone. We fit linear time-series regression to model the relationship. Results Average Rt was 1.06 (95% confidence interval [CI], 1.02–1.11). A mean of 2.92 violent events resulted in cumulative absolute increase in Rt of 0.10 (95% CI, .05–.15). More violent events increased EBOV transmission (P = .03). Considering violent events in the 95th percentile over a 21-day interval and its relative impact on Rt, Ebola-targeted events corresponded to Rt of 1.52 (95% CI, 1.30–1.74), while civilian-induced events corresponded to Rt of 1.43 (95% CI, 1.21–1.35). Untargeted events corresponded to Rt of 1.18 (95% CI, 1.02–1.35); among these, militia/political or ville morte events increased transmission. Conclusions Ebola-targeted violence, primarily driven by civilian-induced events, had the largest impact on EBOV transmission., A time-series study of the 2018–2020 Ebola virus disease outbreak in the Democratic Republic of the Congo found both Ebola-targeted and untargeted violence increased transmission, though targeted violence, primarily driven by civilian-involved events, had the largest impact.

Background Varicella zoster virus (VZV) causes both varicella (chickenpox) and herpes zoster (shingles) and is associated with significant global morbidity. Most epidemiological data on VZV come from high-income countries, and to date there are limited data on the burden of VZV in Africa. Methods We assessed the seroprevalence of VZV antibodies among children in the Democratic Republic of Congo in collaboration with the 2013-2014 Demographic and Health Survey. Dried blood spot samples collected from children 6-59 months of age were run on Dynex™ Technologies Multiplier FLEX® chemiluminescent immunoassay platform to assess serologic response. Multivariate logistic regression was then used to determine risk factors for VZV seropositivity. Results Serologic and survey data were matched for 7,195 children 6-59 months of age, among whom 8% were positive and 2% indeterminate for VZV antibodies in weighted analyses. In multivariate analyses, the odds of seropositivity increased with increasing age, increasing socioeconomic status, mother's education level, rural residence, and province (South Kivu, North Kivu, Bandundu, Bas Congo had the highest odds of a positive test result compared with Kinshasa). Conclusion Our data suggest that VZV is circulating in DRC, and seropositivity is low among children 6-59 months. Seropositivity increased with age and varied by other sociodemographic factors, such as geographic location. This study provides the first nationally representative estimates of VZV infection among children in the DRC.

Background: Violence can impact Ebola virus disease (EVD) transmission in the current outbreak in the eastern Democratic Republic of the Congo (DRC). We hypothesized that violent events targeted against the Ebola response will be associated with more EVD transmission than untargeted events. Methods: We used a dynamic cohort of individuals who lived in Ebola-affected and unaffected health zones in DRC from April 2018 to August 2019. The time-varying exposure was the number of violent events, as defined by the Armed Conflict Location & Event Data Project (ACLED) database, that occurred in each health zone over a series of days. These violent events were categorized into "Ebola-targeted" vs. "Ebola-untargeted", and further sub-categorized by "civilians," "military or politics," or "protests." The outcome variable was the estimated daily reproduction number (Rest) by health zone, which was estimated from daily EVD case counts (from DRC Ministry of Health) by the Wallinga-Teunis method. We fit a linear time-series regression to model the relationship of violent events and R comparing EVD-affected and unaffected health zones. Findings: The average Rest was 1.06 (95% confidence interval [CI]: 1.02-1.11). We found an overall change in R of 0.035 (95% CI: 0.020-0.050) among Ebola-affected compared to unaffected health zones. Violent events targeting the Ebola response were associated with an increase in Rest of 0.098 (95% CI: 0.064-0.132) while untargeted, violent events had a smaller effect (0.022, 95% CI: 0.005-0.038). Additional analyses showed the increase in Rest was primarily driven by Ebola-targeted civilian events and, to a lesser extent, by Ebola-untargeted military, political, or protest events. Interpretation: These findings suggest that civilian acts of violence directly targeted against the Ebola response efforts had the largest impact on EVD transmission. To a lesser extent, untargeted military, political, or protest events also had an impact. Funding Statement: This work was supported by National Institute of Allergy and Infectious Disease (K08 grant number AI139361 to ETR; K23 grant number AI135037 to JDK) and National Institute of General Medical Sciences (R01 grant number GM130900 to TCP, JDK, and ETR). Declaration of Interests: The authors stated: "None to declare." Ethics Approval Statement: The authors stated: "Data were publicly available and de-identified, so ethics committee approval was not needed."

As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration.

BackgroundAs of May 27, 2018, 54 cases of Ebola virus disease (EVD) were reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the current outbreak size and duration with and without vaccine use.MethodsWe modeled Ebola virus transmission using a stochastic branching process model with a negative binomial distribution, using both estimates of reproduction number R declining from supercritical to subcritical derived from past Ebola outbreaks, as well as a particle filtering method to generate a probabilistic projection of the future course of the outbreak conditioned on its reported trajectory to date; modeled using 0%, 44%, and 62% estimates of vaccination coverage. Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize a regression model predicting the outbreak size from the number of observed cases from April 4 to May 27.ResultsWith the stochastic transmission model, we projected a median outbreak size of 78 EVD cases (95% credible interval: 52, 125.4), 86 cases (95% credible interval: 53, 174.3), and 91 cases (95% credible interval: 52, 843.5), using 62%, 44%, and 0% estimates of vaccination coverage. With the regression model, we estimated a median size of 85.0 cases (95% prediction interval: 53.5, 216.6).ConclusionsThis outbreak has the potential to be the largest outbreak in DRC since 2007. Vaccines are projected to limit outbreak size and duration but are only part of prevention, control, and care strategies.

Experimental studies have suggested a larger inoculum of monkeypox virus may be associated with increased rash severity; however, little data are available on the relationship between specific animal exposures and rash severity in endemic regions. Using cross-sectional data from an active surveillance program conducted between 2005 and 2007 in the Sankuru Province of the Democratic Republic of the Congo, we explored the possible relationship between rash severity and exposures to rodents and non-human primates among confirmed MPX cases. Among the 223 PCR-confirmed MPX cases identified during active surveillance, the majority of cases (n = 149) presented with mild rash (5–100 lesions) and 33% had a more serious presentation (> 100 lesions). No association between exposure to rodents and rash severity was found in the multivariable analysis. Those that self-reported hunting NHP 3 weeks prior to onset of MPX symptoms had 2.78 times the odds of severe rash than those that did not report such exposure (95% CI: 1.18, 6.58). This study provides a preliminary step in understanding the association between animal exposure and rash severity and demonstrates correlation with exposure to NHPs and human MPX presentation. Additional research exploring the relationship between rash severity and NHPs is warranted.

BACKGROUND Ebola virus disease (EVD) can be clinically severe and highly fatal, making surveillance efforts for early disease detection of paramount importance. In areas with limited access to laboratory testing, the Integrated Disease Surveillance and Response (IDSR) strategy in the Democratic Republic of Congo (DRC) may be a vital tool in improving outbreak response. METHODS Using DRC IDSR data from the nation's four EVD outbreak periods from 2007-2014, we assessed trends of Viral Hemorrhagic Fever (VHF) and EVD differential diagnoses reportable through IDSR. With official case counts from active surveillance of EVD outbreaks, we assessed accuracy of reporting through the IDSR passive surveillance system. RESULTS Although the active and passive surveillance represent distinct sets of data, the two were correlated, suggesting that passive surveillance based only on clinical evaluation may be a useful predictor of true cases prior to laboratory confirmation. There were 438 suspect VHF cases reported through the IDSR system and 416 EVD cases officially recorded across the outbreaks examined. CONCLUSION Although collected prior to official active surveillance cases, case reporting through the IDSR during the 2007, 2008 and 2012 outbreaks coincided with official EVD epidemic curves. Additionally, all outbreak areas experienced increases in suspected cases for both malaria and typhoid fever during EVD outbreaks, underscoring the importance of training health care workers in recognising EVD differential diagnoses and the potential for co-morbidities.