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: Malnutrition is identified as a risk factor for insufficient polio seroconversion in the context of a vaccine-derived poliovirus (VDPV) outbreak-prone region. In the Democratic Republic of Congo (DRC), underweight decreased from 31% (in 2001) to 26% (in 2018). Since 2004, VDPV serotype 2 outbreaks (cVDPV2) have been documented and were geographically limited around the Haut-Lomami and Tanganyika Provinces. METHODS: To develop and validate a predictive model for poliomyelitis vaccine response in malnourished infants, a cross-sectional household study was carried out in the Haut-Lomami and Tanganyika provinces. Healthy children aged 6 to 59 months (n=968) were enrolled from eight health zones (HZ) out of 27, in March 2018. We performed a bivariate and multivariate logistics analysis. Final models were selected using a stepwise Wald method, and variables were selected based on the criterion p < 0.05. The association between nutritional variables, explaining polio seronegativity for the three serotypes, was assessed using the receiver operating characteristic curve (ROC curve). RESULTS: Factors significantly associated with seronegativity to the three polio serotypes were underweight, non-administration of vitamin A, and the age group of 12 to 59 months. The sensitivity was 10.5%, and its specificity was 96.4% while the positive predictive values (PPV) and negative (PNV) were 62.7% and 65.3%, respectively. We found a convergence of the curves of the initial sample and two split samples. Based on the comparison of the overlapping confidence intervals of the ROC curve, we concluded that our prediction model is valid. CONCLUSION: This study proposed the first tool which variables are easy to collect by any health worker in charge of vaccination or in charge of nutrition. It will bring on top, the collaboration between the Immunization and the Nutritional programs in DRC integration policy, and its replicability in other low- and middle-income countries with endemic poliovirus.

The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with an R² value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses.

BACKGROUND: Malnutrition is identified as a risk-factor for insufficient polioseroconversion in the context of a vaccine-derived polio virus (VDPV) outbreak prone region. To assess the prevalence of malnutrition and its link to poliovirus insufficient immunity, a cross-sectional household survey was conducted in the regions of Haut- Lomami and Tanganyika, DRC. METHODS: In March 2018, we included 968 healthy children aged 6 to 59 months from eight out of 27 districts. Selection of study locations within these districts was done using a stratified random sampling method, where villages were chosen based on habitat characteristics identified from satellite images. Consent was obtained verbally in the preferred language of the participant (French or Swahili) by interviewers who received specific training for this task. Furthermore, participants contributed a dried blood spot sample, collected via finger prick. To assess malnutrition, we measured height and weight, applying WHO criteria to determine rates of underweight, wasting, and stunting. The assessment of immunity to poliovirus types 1, 2, and 3 through the detection of neutralizing antibodies was carried out at the CDC in Atlanta, USA. RESULTS: Of the study population, we found 24.7% underweight, 54.8% stunted, and 15.4% wasted. With IC95%, underweight (OR=1.50; [1.11-2.03]), and the non-administration of vitamin A (OR=1.96; [1.52-2.54]) were significantly associated with seronegativity to polioserotype 1. Underweight (OR=1.64; [1.20-2.24]) and the non-administration of vitamin A (OR=1.55; [1.20-2.01]) were significantly associated with seronegativity to polioserotype 2. Underweight (OR=1.50; [1.11-2.03]), and the non-administration of vitamin A (OR=1.80. [1.38-2.35]) were significantly associated with seronegativity to polioserotype 3. Underweight (OR=1.68; IC95% [1.10-2.57]) and the non-administration of vitamin A (OR=1.82; IC95% [1.30-2.55]) were significantly associated with seronegativity to all polioserotypes. CONCLUSION: This study reveals a significant association between underweight and polioseronegativity in children. In order to reduce vaccine failures in high-risk areas, an integrated approach by vaccination and nutrition programs should be adopted.

Despite the successes in wild-type polio eradication, poor vaccine coverage in the DRC has led to the occurrence of circulating vaccine-derived poliovirus outbreaks. This cross-sectional population-based survey provides an update to previous poliovirus-neutralizing antibody seroprevalence studies in the DRC and quantifies risk factors for under-immunization and parental knowledge that guide vaccine decision making. Among the 964 children between 6 and 35 months in our survey, 43.8% (95% CI: 40.6-47.0%), 41.1% (38.0-44.2%), and 38.0% (34.9-41.0%) had protective neutralizing titers to polio types 1, 2, and 3, respectively. We found that 60.7% of parents reported knowing about polio, yet 25.6% reported knowing how it spreads. Our data supported the conclusion that polio outreach efforts were successfully connecting with communities-79.4% of participants had someone come to their home with information about polio, and 88.5% had heard of a polio vaccination campaign. Additionally, the odds of seroreactivity to only serotype 2 were far greater in health zones that had a history of supplementary immunization activities (SIAs) compared to health zones that did not. While SIAs may be reaching under-vaccinated communities as a whole, these results are a continuation of the downward trend of seroprevalence rates in this region.

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.

Healthcare settings have played a major role in propagation of Ebola virus (EBOV) outbreaks. Healthcare workers (HCWs) have elevated risk of contact with EBOV-infected patients, particularly if safety precautions are not rigorously practiced. We conducted a serosurvey to determine seroprevalence against multiple EBOV antigens among HCWs of Boende Health Zone, Democratic Republic of the Congo, the site of a 2014 EBOV outbreak. Interviews and specimens were collected from 565 consenting HCWs. Overall, 234 (41.4%) of enrolled HCWs were reactive to at least 1 EBOV protein: 159 (28.1%) were seroreactive for anti-glycoprotein immunoglobulin G (IgG), 89 (15.8%) were seroreactive for anti-nucleoprotein IgG, and 54 (9.5%) were VP40 positive. Additionally, sera from 16 (2.8%) HCWs demonstrated neutralization capacity. These data demonstrate that a significant proportion of HCWs have the ability to neutralize virus, despite never having developed Ebola virus disease symptoms, highlighting an important and poorly documented aspect of EBOV infection and progression.

Introduction

As of April 2019, the current Ebola virus disease (EVD) outbreak in the Democratic Republic of the Congo (DRC) is occurring in a longstanding conflict zone and has become the second largest EVD outbreak in history. It is suspected that after violent events occur, EVD transmission will increase; however, empirical studies to understand the impact of violence on transmission are lacking. Here, we use spatial and temporal trends of EVD case counts to compare transmission rates between health zones that have versus have not experienced recent violent events during the outbreak.

Methods

We collected daily EVD case counts from DRC Ministry of Health. A time-varying indicator of recent violence in each health zone was derived from events documented in the WHO situation reports. We used the Wallinga-Teunis technique to estimate the reproduction number R for each case by day per zone in the 2018-2019 outbreak. We fit an exponentially decaying curve to estimates of R overall and by health zone, for comparison to past outbreaks.

Results

As of 16 April 2019, the mean overall R for the entire outbreak was 1.11. We found evidence of an increase in the estimated transmission rates in health zones with recently reported violent events versus those without (p = 0.008). The average R was estimated as between 0.61 and 0.86 in regions not affected by recent violent events, and between 1.01 and 1.07 in zones affected by violent events within the last 21 days, leading to an increase in R between 0.17 and 0.53. Within zones with recent violent events, the mean estimated quenching rate was lower than for all past outbreaks except the 2013-2016 West African outbreak.

Conclusion

The difference in the estimated transmission rates between zones affected by recent violent events suggests that violent events are contributing to increased transmission and the ongoing nature of this outbreak.

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.

The first reported outbreak of Ebola virus disease occurred in 1976 in Yambuku, Democratic Republic of Congo. Antibody responses in survivors 11 years after infection have been documented. However, this report is the first characterization of anti-Ebola virus antibody persistence and neutralization capacity 40 years after infection. Using ELISAs we measured survivor's immunological response to Ebola virus Zaire (EBOV) glycoprotein and nucleoprotein, and assessed VP40 reactivity. Neutralization of EBOV was measured using a pseudovirus approach and plaque reduction neutralization test with live EBOV. Some survivors from the original EBOV outbreak still harbor antibodies against all 3 measures. Interestingly, a subset of these survivors' serum antibodies could still neutralize live virus 40 years postinitial infection. These data provide the longest documentation of both anti-Ebola serological response and neutralization capacity within any survivor cohort, extending the known duration of response from 11 years postinfection to at least 40 years after symptomatic infection.