The duration of immunity after first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the extent to which prior immunity prevents reinfection is uncertain and remains an important question within the context of new variants. This is a retrospective population-based matched observational study where we identified the first polymerase chain reaction (PCR) positive of primary SARS-CoV-2 infection case tests between 1 March 2020 and 30 September 2020. Each case was matched by age, sex, upper tier local authority of residence and testing route to one individual testing negative in the same week (controls) by PCR. After a 90-day pre-follow-up period for cases and controls, any subsequent positive tests up to 31 December 2020 and deaths within 28 days of testing positive were identified, this encompassed an essentially vaccine-free period. We used a conditional logistic regression to analyse the results. There were 517 870 individuals in the matched cohort with 2815 reinfection cases and 12 098 first infections. The protective effect of a prior SARS-CoV-2 PCR-positive episode was 78% (odds ratio (OR) 0.22, 0.21-0.23). Protection rose to 82% (OR 0.18, 0.17-0.19) after a sensitivity analysis excluded 933 individuals with a first test between March and May and a subsequent positive test between June and September 2020. Amongst individuals testing positive by PCR during follow-up, reinfection cases had 77% lower odds of symptoms at the second episode (adjusted OR 0.23, 0.20-0.26) and 45% lower odds of dying in the 28 days after reinfection (adjusted OR 0.55, 0.42-0.71). Prior SARS-CoV-2 infection offered protection against reinfection in this population. There was some evidence that reinfections increased with the alpha variant compared to the wild-type SARS-CoV-2 variant highlighting the importance of continued monitoring as new variants emerge.

Introduction Visceral leishmaniasis (VL) is endemic in South Sudan, where outbreaks occur frequently. Because of changes in the immune system during pregnancy, pregnant women are considered particularly vulnerable for developing complications of VL disease, including opportunistic infections. There is limited evidence available about clinical aspects and treatment outcomes of VL in pregnancy. We describe characteristics, maternal and pregnancy outcomes from a cohort of pregnant women with VL. Methods We conducted a retrospective analysis using routine programme data from a MSF health facility in Lankien, Jonglei State, South Sudan, between Oct 2014 and April 2018. Records were extracted of women diagnosed with VL while pregnant, and those symptomatic during pregnancy but diagnosed during the first two weeks postpartum. Records were matched with a random sample of non-pregnant women of reproductive age (15–45 years) with VL from the same period. Results We included 113 women with VL in pregnancy, and 223 non-pregnant women with VL. Women with VL in pregnancy presented with more severe anaemia, were more likely to need blood transfusion (OR 9.3; 95%CI 2.5–34.2) and were more often prescribed antibiotics (OR 6.0; 95%CI 3.4–10.6), as compared to non-pregnant women with VL. Adverse pregnancy outcomes, including miscarriage and premature delivery, were reported in 20% (16/81) where VL was diagnosed in pregnancy, and 50% 13/26) where VL was diagnosed postpartum. Postpartum haemorrhage was common. Pregnant women were more likely to require extension of treatment to achieve cure (OR 10.0; 95%CI 4.8–20.9), as compared to non-pregnant women with VL. Nevertheless, overall initial cure rates were high (96.5%) and mortality was low (1.8%) in this cohort of pregnant women with VL. Conclusion This is the largest cohort in the literature of VL in pregnancy. Our data suggest that good maternal survival rates are possible in resource-limited settings, despite the high incidence of complications.

Improving access to care for survivors of sexual violence: key lessons from two mixed-methods studies, Haiti and India presented at MSF Scientific Days International (London) Medical Research Day, May 13, 2020 by Meggy Verputten

Between August and December 2017, more than 625,000 Rohingya from Myanmar fled into Bangladesh, settling in informal makeshift camps in Cox’s Bazar district and joining 212,000 Rohingya already present. In early November, a diphtheria outbreak hit the camps, with 440 reported cases during the first month. A rise in cases during early December led to a collaboration between teams from Médecins sans Frontières—who were running a provisional diphtheria treatment centre—and the London School of Hygiene and Tropical Medicine with the goal to use transmission dynamic models to forecast the potential scale of the outbreak and the resulting resource needs. We first adjusted for delays between symptom onset and case presentation using the observed distribution of reporting delays from previously reported cases. We then fit a compartmental transmission model to the adjusted incidence stratified by age group and location. Model forecasts with a lead time of 2 weeks were issued on 12, 20, 26 and 30 December and communicated to decision-makers. The first forecast estimated that the outbreak would peak on 19 December in Balukhali camp with 303 (95% posterior predictive interval 122–599) cases and would continue to grow in Kutupalong camp, requiring a bed capacity of 316 (95% posterior predictive interval (PPI) 197–499). On 19 December, a total of 54 cases were reported, lower than forecasted. Subsequent forecasts were more accurate: on 20 December, we predicted a total of 912 cases (95% PPI 367–2183) and 136 (95% PPI 55–327) hospitalizations until the end of the year, with 616 cases actually reported during this period. Real-time modelling enabled feedback of key information about the potential scale of the epidemic, resource needs and mechanisms of transmission to decision-makers at a time when this information was largely unknown. By 20 December, the model generated reliable forecasts and helped support decision-making on operational aspects of the outbreak response, such as hospital bed and staff needs, and with advocacy for control measures. Although modelling is only one component of the evidence base for decision-making in outbreak situations, suitable analysis and forecasting techniques can be used to gain insights into an ongoing outbreak.

The Katanga region in the Democratic Republic of Congo (DRC) has been struck by repeated epidemics of measles, with large outbreaks occurring in 2010–13 and 2015. In many of the affected health zones, reactive mass vaccination campaigns were conducted in response to the outbreaks. Here, we attempted to determine how effective the vaccination campaigns in 2015 were in curtailing the ongoing outbreak. We further sought to establish whether the risk of large measles outbreaks in different health zones could have been determined in advance to help prioritise areas for vaccination campaign and speed up the response. In doing so, we first attempted to identify factors that could have been used in 2015 to predict in which health zones the greatest outbreaks would occur. Administrative vaccination coverage was not a good predictor of the size of outbreaks in different health zones. Vaccination coverage derived from surveys, on the other hand, appeared to give more reliable estimates of health zones of low vaccination coverage and, consequently, large outbreaks. On a coarser geographical scale, the provinces most affected in 2015 could be predicted from the outbreak sizes in 2010–13. This, combined with the fact that the vast majority of reported cases were in under-5 year olds, would suggest that there are systematic issues of undervaccination. If this was to continue, outbreaks would be expected to continue to occur in the affected health zones at regular intervals, mostly concentrated in under-5 year olds. We further used a model of measles transmission to estimate the impact of the vaccination campaigns, by first fitting a model to the data including the campaigns and then re-running this without vaccination. We estimated the reactive campaigns to have reduced the size of the overall outbreak by approximately 21,000 (IQR: 16,000–27,000; 95% CI: 8300–38,000) cases. There was considerable heterogeneity in the impact of campaigns, with campaigns started earlier after the start of an outbreak being more impactful. Taken together, these findings suggest that while a strong routine vaccination regime remains the most effective means of measles control, it might be possible to improve the effectiveness of reactive campaigns by considering predictive factors to trigger a more targeted vaccination response.

Background Provision of antiretroviral therapy (ART) in conflict settings is rarely attempted and little is known about the expected patterns of mortality. The Central African Republic (CAR) continues to have a low coverage of ART despite an estimated 110,000 people living with HIV and 5000 AIDS-related deaths in 2018. We present results from a cohort in Zemio, Haut-Mboumou prefecture. This region had the highest prevalence of HIV nationally (14.8% in a 2010 survey), and was subject to repeated attacks by armed groups on civilians during the observed period. Methods Conflict from armed groups can impact cohort mortality rates i) directly if HIV patients are victims of armed conflict, or ii) indirectly if population displacement or fear of movement reduces access to ART. Using monthly counts of civilian deaths, injuries and abductions, we estimated the impact of the conflict on patient mortality. We also determined patient-level risk factors for mortality and how the risk of mortality varies with time spent in the cohort. Model-fitting was performed in a Bayesian framework, using logistic regression with terms accounting for temporal autocorrelation. Results Patients were recruited and observed in the HIV treatment program from October 2011 to May 2017. Overall 1631 patients were enrolled and 1628 were included in the analysis giving 48,430 person-months at risk and 145 deaths. The crude survival rate after 12 months was 0.92 (95% CI 0.90, 0.93). Our model showed that patient mortality did not increase during periods of heightened conflict; the odds ratios (OR) 95% credible interval (CrI) for i) civilian fatalities and injuries, and ii) civilian abductions on patient mortality both spanned unity. The risk of mortality for individual patients was highest in the second month after entering the cohort, and declined seven-fold over the first 12 months. Male sex was associated with a higher mortality (odds ratio 1.70 [95% CrI 1.20, 2.33]) along with the severity of opportunistic infections (OIs) at baseline (OR 2.52; 95% CrI 2.01, 3.23 for stage 2 OIs compared with stage 1). Conclusions Our results show that chronic conflict did not appear to adversely affect rates of mortality in this cohort, and that mortality was driven predominantly by patient-specific risk factors. The risk of mortality and recovery of CD4 T-cell counts observed in this conflict setting are comparable to those in stable resource poor settings, suggesting that conflict should not be a barrier in access to ART.

This abstract corresponds with the following video: https://f1000research.com/videos/7-834 presented at Médecins Sans Frontières UK Scientific Days: Medical Research 2018. This abstract is part of an F1000Research gateway that includes posters, slides and videos from the MSF Scientific Day: Medical Research 2018. To see more please visit: https://f1000research.com/gateways/MSF/scidays

Background Hepatitis E Virus (HEV) is an important cause of morbidity and mortality in emergency and refugee camp settings. Symptomatic infection is associated with case fatality rates of ~20% in pregnant women. However, its epidemiology is poorly understood and the potential impact of immunisation in outbreak settings uncertain. We aimed to estimate key epidemiological parameters for HEV and to evaluate the potential impact of both reactive vaccination (initiated in response to an epidemic) and pre-emptive vaccination. Methods We analysed data from one of the world’s largest recorded HEV epidemics, which occurred in refugee camps in Uganda (2007-2009), using transmission dynamic models to estimate epidemiological parameters and assess the potential impact of reactive and pre-emptive vaccination strategies. Results Under baseline assumptions we estimated the basic reproduction number of HEV to range from 3.9 (95% CrI 2.8, 5.4) to 8.9 (5.4, 14.2). Mean latent and infectious periods were estimated to be 34 (28, 39) and 40 (23, 71) days respectively. Reactive two-dose vaccination of those aged 16-65 years excluding pregnant women (for whom vaccine is not licensed), if initiated after 50 reported cases, led to mean camp-specific reductions in mortality of 10 to 29%. Pre-emptive vaccination with two doses reduced mortality by 35 to 65%. Both strategies were more effective if coverage was extended to groups for whom the vaccine is not currently licensed. For example, two dose pre-emptive vaccination, if extended to include pregnant women, led to mean reductions in mortality of 66 to 82%. Conclusions HEV has a high transmission potential in refugee camp settings. Substantial reductions in mortality through vaccination are expected, even if used reactively. There is potential for greater impact if vaccine safety and effectiveness can be established in pregnant women. Funding Wellcome Trust (106491/Z/14/Z and 089275/Z/09/Z). BC: MRC/DfID (MR/K006924/1).

A high incidence of bacterial meningitis was observed in the Central African Republic (CAR) from December 2015 to May 2017 in three hospitals in the northwest of the country that are within the African meningitis belt. The majority of cases were caused by Streptococcus pneumoniae (249/328; 75.9%), which occurred disproportionately during the dry season (November-April) with a high case-fatality ratio of 41.6% (95% confidence interval [CI] 33.0, 50.8%). High rates of bacterial meningitis during the dry season in the meningitis belt have typically been caused by Neisseria meningitidis (meningococcal meningitis), and our observations suggest that the risk of contracting S. pneumoniae (pneumococcal) meningitis is increased by the same environmental factors. Cases of meningococcal meningitis (67/328; 20.4%) observed over the same period were predominantly group W and had a lower case fatality rate of 9.6% (95% CI 3.6, 21.8%). Due to conflict and difficulties in accessing medical facilities, it is likely that the reported cases represented only a small proportion of the overall burden. Nationwide vaccination campaigns in the CAR against meningitis have been limited to the use of MenAfriVac, which targets only meningococcal meningitis group A. We therefore highlight the need for expanded vaccine coverage to prevent additional causes of seasonal outbreaks.

This presentation discusses potential impacts of an emergency vaccination to control hepatitis E infection in refugee settings.

Bentiu protection of civilians (PoC) camps was set up by the UN mission in South Sudan in 2013 to protect civilians at risk being targeted by warring parties. MSF helps provide secondary health care and activities related to water, sanitation and hygiene promotion and have also opened a cholera treatment centre. This poster describes the results and conclusions drawn from a descriptive analysis performed on the surveillance data recorded at the cholera treatment centre.

MSF returned back to Mweso, Democratic Republic of Congo, in 2016 and since noticed a high mortality in the neonatal ward. Having suspected a meningitis outbreak, epidemiological investigations found that 29% of neonates were admitted to the ward without good indication. In addition to this, different investigations found that there was in fact, no indication of a meningitis/sepsis outbreak. Improved training and supervision are being implemented.

The Central African Republic (CAR) has low access to anti-retroviral therapy (ART), facing a number of challenges in healthcare provision including instability and civil conflict, along with a lack of infrastructure outside of the capital Bangui. Consequently, mortality rate per 1000 people living with HIV is the highest in the world. These MSF researchers detail treatment outcomes from a HIV patient cohort on a program of ART provision in a rural setting in CAR for >5 years, reporting a resulting survival rate after 12 months equal to or greater than values reported from studies in more stable African settings.

Integrated Community Case Management (iCCM) and Partially Supported Health Structure (PHS) programmes are a part of MSF interventions, targeting diarrhoea and respiratory infections in children aged less than 5, as well as malaria in all ages. Since these programmes started in 2014, mortality surveys and analysis have shown a dramatic decrease in both crude and under 5 mortality rates. Despite this, mortality rates continue to lie above emergency thresholds.

This abstract corresponds with the following slides: https://f1000research.com/slides/6-692, presented at Médecins Sans Frontières UK Scientific Days: Innovation 2017. To watch the presentation click here: https://f1000research.com/videos/6-808. This abstract is part of an F1000Research gateway that includes posters, slides and videos from the MSF Scientific Day: Innovation 2017. To see more please visit: https://f1000research.com/gateways/MSF/innovation.

Between 2009 and 2012, malaria cases diagnosed in a Médecins sans Frontières programme have increased fivefold in Baraka, South Kivu, Democratic Republic of the Congo (DRC). The cause of this increase is not known. An in vivo drug efficacy trial was conducted to determine whether increased treatment failure rates may have contributed to the apparent increase in malaria diagnoses.

Current WHO testing guidelines for resource limited settings diagnose HIV on the basis of screening tests without a confirmation test due to cost constraints. This leads to a potential risk of false positive HIV diagnosis. In this paper, we evaluate the dilution test, a novel method for confirmation testing, which is simple, rapid, and low cost. The principle of the dilution test is to alter the sensitivity of a rapid diagnostic test (RDT) by dilution of the sample, in order to screen out the cross reacting antibodies responsible for falsely positive RDT results.