Description of a large and deadly measles epidemic, Yakusu health zone, Democratic Republic of Congo, 2018-2019: A retrospective study

Description of a large and deadly measles epidemic, Yakusu health zone, Democratic Republic of Congo, 2018-2019: A retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Description of a large and deadly measles epidemic, Yakusu health zone, Democratic Republic of Congo, 2018-2019: A retrospective study Franck Alé, M. Eugenia Riccio, Yves Katuala, Théophile Maloko, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6878790/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background A large measles outbreak occurred in Yakusu Health Zone, Democratic Republic of the Congo, between Jan 2018 and June 2019. We describe the extent of the outbreak and it’s impact on the population. Methods We conducted a retrospective household survey to describe the attack rate and various mortality measures, and to assess vaccination coverage both before and after a mass reactive vaccination campaign. We estimated the true outbreak size by extrapolating the attack rate and case fatality ratios to the population of Yakusu. We conducted geospatial analyses to describe the distribution of measles attack rate and vaccination coverage. Results 8,968 individuals were included in the survey, of whom 1,390 (15.5%, 95%CI 13.2-17.8) reported to have had measles during the recall period. The outbreak size was estimated as 22,068 (95% CI 18,980-25,553). Overall case fatality ratio was 2.5% [95% CI 1.7-3.4]; measles-specific proportional mortality was 15.3% [95%CI 10.9-19.8]; and the all-cause mortality rate was 0.72 per 10,000 person-days [95% CI 0.61-0.82]. For children aged under 5 years, the overall attack rate was 45.7% [95% CI 39.6-51.9]; case fatality ratio was 4.9% [95% CI 3.4-6.3]; measles-specific proportional mortality was 35.2% [95%CI 26.0-44.5]; and all-cause mortality rate was 1.51 per 10,000 person-days [95% CI 1.19-1.84]. Children aged under 1 year had the greatest risk of death. Two-thirds of the target population had been vaccinated during routine Expanded Programme on Immunization (EPI, 67.9% [95%CI 62.2-73.6]) and during the campaign (67.7% [95%CI 61.6-73.8]). Coverage according to either EPI or campaign was 82.1% [95%CI 78.0-86.1]). There was a high degree of spatial overlap in vaccination coverage by EPI and campaign, with pockets of low coverage throughout Yakusu, within which the epidemic propagated. Conclusions This was a high-impact epidemic, both in terms of attack rate and case fatality, with an elevated risk of dying for at least 90 days post-onset of disease. Reactive vaccination activities were effective at the individual level, but were implemented late, did not reach intended coverage, and were insufficiently targeted to ensure that previously unvaccinated children received vaccination, thereby leaving pockets of unvaccinated children among whom the outbreak appeared to persist. Epidemiology Measles Disease Outbreaks Mass Vaccination Vaccination Coverage Retrospective Studies Health Surveys Mortality Figures Figure 1 Figure 2 Figure 3 Introduction Measles was historically a major contributor to child morbidity and mortality globally prior to the widespread implementation of a highly effective vaccine [ 1 ]. Following enormous progress in measles elimination in the latter years of the 20th century, measles incidence continued to decrease considerably in the 21st century, from 145 to 17 cases per million people between 2000 and 2021 [ 2 ]. This progress was accompanied by a concomitant decline in annual measles-related deaths, decreasing from an estimated 761,000 to 128,000, averting an estimated 56 million deaths [ 2 ]. Despite these achievements, measles epidemics persist, particularly in sub-Saharan Africa [ 2 , 3 ]. Due to the combined effects of low vaccination coverage, inadequate surveillance, and a struggling healthcare system, the Democratic Republic of the Congo (DRC) experienced between 2018–2019 one of the largest measles outbreaks ever recorded, with 311,471 reported cases [ 4 ]. Médecins Sans Frontières (MSF), in collaboration with the DRC Ministry of Public Health (MoH), responded to this crisis by reinforcing surveillance, providing free medical care, and conducting vaccination campaigns. Yakusu Health Zone (HZ), Tshopo province, was one the most affected areas. Out of an estimated population of 142,379, 6,150 measles cases (attack rate [AR]: 4.3%) and 152 measles-attributable deaths (case fatality ratio [CFR]: 2.5%) were reported between Jan 1 2018 and 30 June 2019 (Fig. 1 ). During the peak of the epidemic, between 3 March and 20 April 2019, MSF supported the MoH by providing free treatment to a total of 2,615 patients (Fig. 1 ). Additionally, between 7–20 April, MoH conducted a mass vaccination campaign (MVC) targeting all children aged 6–59 months. Due to limited access to healthcare, weak disease surveillance systems, and incomplete health records leading to under-attribution of measles as cause of death [ 5 , 6 ], the reported AR and CFR were likely substantially underestimated. Therefore, this study aims to document the impact of the outbreak by estimating several key parameters for both the overall population and among children aged under 5 years (under-5s) specifically: the AR; CFR; measles-specific proportional mortality (MSPM); and the daily crude and under-5 mortality rates (CMR and U5MR, respectively). Methods Study design and setting This was a cross-sectional two-stage cluster survey, conducted in Yakusu HZ from 2–9 July 2019. The target population was any person residing for at least four weeks in Yakusu HZ during the recall period (from 1 January 2018 until the date of data collection). Sampling method Households were chosen using two-stage cluster sampling as recommend by WHO [ 9 ]. At the first stage, 40 clusters were selected with a probability proportional to the size of the village or quarter from which the cluster was selected. At the second stage, 25 households were selected by randomly generating GPS points within the perimeter of the village or quarter from which the cluster was selected. When the perimeter of the village or quarter was unknown or incorrect, a systematic random sample was included instead. In villages where there were fewer than 25 households, all households were selected for inclusion. Tablets provided to each surveyor team were equipped with OsmAnd (OSM Automated Navigation Directions) [ 7 ] software to identify the household closest to each randomly generated GPS points in order to start household selection within each cluster. Subsequent households were selected based on proximity to the prior household using a defined protocol. Data collection Information was collected on demographic characteristics, measles vaccination and infection status, and, where appropriate, access to healthcare and cause of death, for all individuals (Supplementary information). Surveyors underwent a 3-day training on household selection, obtaining informed consent, and conducting the survey through practical work and role play. A pilot study was conducted outside of the survey target area to test and adapt the survey material to the local context. Interviews were conducted in Lingala or Swahili, the local languages. Community leaders and heads of households were informed about the survey several days before the planned site visits and the interview date was arranged with those household respondents willing to participate. On the interview date, eight teams comprising two surveyors each visited the selected households, explained the survey objectives to the primary respondent, and obtained informed consent to participate. If consent was provided, all household members were included in the survey. Participation refusals were recorded in logbooks. Data were collected on mobile devices using KoBoCollect software [ 8 ]. Main definitions A measles case was defined as any individual with the following symptoms: maculopapular rash during at least 3 days, ≥ 38°C fever (or warm to the touch), and cough or upper respiratory tract infection or conjunctivitis. A measles-specific death was defined as any death occurring within 31 days of onset of measles symptoms [ 9 ]. As there is increasing evidence that elevated measles mortality may persist for longer than this, we also performed a sensitivity analysis for mortality over an extended period, using an alternative definition for a measles-specific death as any death occurring within 90 days of onset of measles symptoms. Data analysis Measles IR was calculated as the number of cases divided by the average person-time at-risk during one year, expressed as cases per 1000 person-years. Measles AR was calculated as the number of measles cases divided by the number of persons included in the survey during the recall period. CFR was calculated as the number of measles-specific deaths divided by the number of measles cases. MSPM was calculated as the number of measles-attributable deaths divided by the total number of deaths recorded. AR, CFR, and MSPM were expressed as percentages. All-cause and measles-specific mortality rates, expressed as deaths per 10,000 person-days, were estimated as the number of (measles-specific) deaths divided by the total person-time at risk multiplied by 10,000. Person-time at risk depended on time spent in the household: for the majority of participants who spent the entire recall period as household members, the exposure period was calculated as the whole recall period; for participants who migrated in or out of the household during the recall period, the exposure period was calculated as half the total recall period; and finally, for any participants who were born and/or died during the recall period, the exposure period was calculated taking these dates into consideration. All analyses were performed for all individuals and separately for children aged under 5 years, who represent the segment of the population most vulnerable to measles and were therefore the target of the reactive vaccination campaign. Additionally, stratified analyses were performed according to three periods, to evaluate the impact of MSF intervention: the period prior to the MSF interventions (Phase 1; 1 Jan 2018–2 March 2019), the period covering the MSF interventions (Phase 2; 3 March – 20 April 2019), and the period between the cessation of MSF’s activities and the survey date (Phase 3; 21 April – 30 June 2019). To describe the risk factors associated with measles mortality, we fitted a log Poisson regression model and used a multilevel model including random effects at cluster and household levels. We included sex, age group, period of onset, and EPI vaccination status as explanatory variables. In the univariate analysis, all variables were tested for association with measles mortality, and those with p < 0.1 were included in the multivariate analysis. To estimate the population-level impact of the outbreak and the proportion of cases and deaths detected by the surveillance system (calculated as the number of cases detected divided by the estimated total number of cases), estimates of the true number of cases and measles-specific deaths within Yakusu HZ were calculated by extrapolation of survey results to the estimated population size. Measles vaccination coverage was estimated as the proportion of individuals reporting having received any dose of the vaccine (either by vaccination card or by parental recall). Coverage was estimated separately for both the routine Expanded Program on Immunization (EPI) which targets children aged 9–11 months, and the Supplementary Immunization Activity (SIA) campaign which targeted children aged 6–59 months. Geospatial analyses were conducted to show spatial distributions of i) EPI and reactive mass campaign coverage, and ii) measles AR, among children aged 6–59 months (the age group targeted for vaccination). Point pattern datasets were created using the R package “Spatstat” [ 13 ], applying cluster-specific estimates of vaccination coverage and AR to the geographic coordinates of each cluster. These data were smoothed using a Gaussian kernel function, and visualized in heat maps [ 10 , 11 ]. All data were analyzed using R statistical software [ 12 ]. Ethics The study protocol was approved by the MSF Ethics Review Board and the Research Ethics Committee of Kisangani University, DRC. The survey was conducted in accordance with the international ethics guidelines for biomedical research involving human subjects and the guidelines for the conduct of epidemiological studies of the Council for International Organization of Medical Science (CIOMS) [ 13 , 14 ]. Various community authorities (including village and religious chiefs and heads of households) were informed of the survey objectives and received a copy of the information sheet in their local language. Verbal consent from the head-of-household was mandatory to participate in the survey. It was clearly stated that all participants were free to withdraw from the study at any time without any consequence. Confidentiality was maintained during the interviewing process. All collected data were pseudo-anonymized (with only first names collected), and electronic files were stored on a password-protected remote server, to which only investigators had access. Results Sample description A total of 1,101 households were selected for participation in the survey, of which 1,080 (98.1%), comprising 8,968 individuals, consented to participate. The mean household size was 9.1 (95% confidence interval [CI]: 8.6–9.5), and the median age was 14 (IQR 5–28), with approximately one-fifth (21.6% [95%CI 20.6–22.5]) of the population aged under 5 years. The male-to-female sex ratio was 1.01 (0.96–1.06). Over three-quarters of the participants (6,905, 77.0%) were present in the household throughout the entire recall period, while 496 (5.5%) joined and 657 (7.3%) left the household during the recall period. There were 724 births and 313 deaths during the recall period (Table 1 ). At the time of the survey, 7,998 individuals (89.2%) were current members of the household. Approximately half (4566, 50.9%) of study participants were aged under 15 years, while there was an even split between males (4505, 50.2%) and females (4463, 49.8%). Table 1 Description of study participants by characteristics, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018–30 June 2019. Characteristic Number (%) Age group <1 years 400 (4.5) 1–4 years 1534 (17.1) 5–9 years 1563 (17.4) 10–14 years 1069 (11.9) ≥15 years 4402 (49.1) Sex Female 4463 (49.8) Male 4505 (50.2) Vaccination (EPI) Not vaccinated 1238 (13.8) Vaccinated 2617 (29.2) Unknown 5113 (57.0) Vaccination (MVC) Not vaccinated 641 (7.1) Vaccinated 1338 (14.9) Unknown 6989 (77.9) Vaccination (EPI &/or MVC) Not vaccinated 341 (3.8) Vaccinated 2929 (32.7) Unknown 5698 (63.5) Measles case Non-case 7578 (84.5) Case 1390 (155.5) Status Alive 8655 (96.5) Dead 313 (3.5) Total 8968 (100) Measles cases After having the standard measles case definition explained to participants, there were 1,390 self-reported cases (Table 2 ), with a temporal distribution that closely matched that described by the routine surveillance data (Fig. 2 ). This yielded respective overall and under 5 ARs of 15.5% [95%CI 13.2–17.8] and 45.7% [95% CI 39.6–51.9] (Table 3 ). In a multivariate analysis, children aged under 5 years had a much higher risk of becoming a case (Risk Ratio [RR] 2.5 [95%CI 2.1–2.9]), while individuals who had received vaccine either by routine EPI or campaign had a significantly lower risk (RR 0.80 [95%CI 0.68–0.93]). Table 2 Description of measles cases and decedents, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018–30 June 2019. Characteristic Cases (%) Deaths (%) Age group <1 years 77 (5.5) 15 (31.3) 1–4 years 807 (58.1) 28 (58.3) 5–9 years 416 (29.9) 4 (8.3) 10–14 years 57 (4.1) 0 (-) ≥15 years 33 (2.4) 1 (2.1) Sex Female 691 (49.7) 21 (43.8) Male 699 (50.3) 27 (56.3) Vaccination (EPI) Not vaccinated 385 (27.7) 14 (29.2) Vaccinated 824 (59.3) 19 (39.6) Unknown 181 (13.0) 15 (31.3) Other cases in HH No 215 (15.5) 10 (20.8) Yes 1175 (84.5) 38 (79.2) Sought care No 287 (20.6) 3 (6.3) Yes 1103 (79.4) 45 (93.8) Total 1390 (100) 48 (100) Table 3 Cases, deaths, CFR, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018–30 June 2019. Study sample Cases (AR% [95%CI]) Deaths (31-days) (CFR% [95%CI]) Deaths (90-days) (CFR% [95%CI]) Age group <1 years 400 77 (19.2 [15.0-23.5]) 15 (19.5 [12.1–26.9]) 18 (23.4 [12.9–33.8]) 1–4 years 1534 807 (52.6 [45.2–60.0]) 28 (3.5 [2.0-4.9]) 38 (4.7 [3.3–6.2]) 5–9 years 1563 416 (26.6 [21.6–31.6]) 4 (1.0 [0.0-1.9]) 5 (1.2 [0.1–2.3]) 10–14 years 1069 57 (5.3 [3.6-7.0]) 0 (-) 0 (-) ≥15 years 4402 33 (0.8 [0.5-1.0]) 1 (3.0 [-2.6-8.6]) 1 (3.0 [-2.68.6]) Classical age groups <5 years 1934 884 (45.7 [39.6–51.9]) 43 (4.9 [3.4–6.3]) 56 (6.3 [4.7–7.9] ≥5 years 7034 506 (7.2 [5.8–8.5]) 5 (1.0 [0.1–1.8]) 6 (1.2 [0.3–2.1]) Sex Female 4463 691 (15.5 [13.2–17.8]) 17 (2.5 [1.4–3.6]) 24 (3.5 [2.2–4.8]) Male 4505 699 (15.5 [12.9–18.1]) 18 (2.6 [1.4–3.7]) 38 (5.4 [3.6–7.2]) Total 8968 1390 (15.5 [13.2–17.8]) 35 (2.5 [1.7–3.4]) 62 (4.5 [3.4–5.5]) Mortality CFR up to 31 days post-onset of symptoms was 3.5% [95% CI 2.5–4.5] overall (48 deaths among 1,390 cases), 4.9% [95% CI 3.4–6.3];) among under 5s (43/884), and 19.5% [95% CI 12.1–26.9]) among under 1s (15/77). However, for deaths within 90 days post-onset, this increased to 4.5% [95%CI 3.38–5.54] (62/1390) overall, 6.3% [95%CI 4.7–7.9] (56/884) among under 5s, and 23.4% [95%CI 12.9–33.8] (18/77) among under 1s. CMR was 0.72 per 10,000 person-days (95% CI 0.62–0.82), while U5MR was 1.51 per 10,000 person-days ([95% CI 1.19–1.84]). Among 313 reported deaths, 48 (15.3% [95%CI 10.9–19.8]) were attributable to measles, and among under 5s, this number was 43 (35.2% [95%CI 26.0-44.5]) of 122 deaths. 90-day all-cause CMR was 0.96 per 10,000 person-days (95%CI 0.71–1.20) for measles patients, compared to 0.66 per 10,000 person-days (95%CI 0.56–0.76) for non-cases (rate difference = 0.30 [95%CI 0.03–0.56], p = 0.028). 90-day all-cause U5MR was 1.46 per 10,000 person-days (95%CI 1.06–1.85) for measles patients, compared to 1.47 per 10,000 person-days (95%CI 1.05–1.89) for non-cases (rate difference = -0.02 [95%CI -0.59-0.56], p = 0.949). MSPM was 15.3% [95%CI 10.9–19.8] overall, 35.2% [95%CI 26.0-44.5] among the under 5s, and 27.3% [95%CI 19.5–35.0] among the under 1s. In the univariate analysis, age group was the only covariate associated with risk of dying from measles; children aged 1–4 years had one eighth the risk of dying from measles compared to under 1s (RR 0.12 [95%CI 0.06–0.28]), while this risk was twenty times lower among individuals aged 5 years and older (RR 0.05 [95%CI 0.02–0.15]) (Table 4 ). Table 4 Multivariable Poisson regression of risk factors for mortality among measles cases, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018–20 April 2019. Variable Univariate analysis Multivariate analysis RR [95%CI] 1 p-value RR [95%CI] p-value Age group 0–1 years ( ref. ) - - - - 1–4 years 0.12 [0.06–0.28] < 0.001* 0.12 [0.06–0.28] < 0.001 5 + years 0.05 [0.02–0.15] < 0.001* 0.05 [0.02–0.15] < 0.001 Sex Female ( ref. ) - - - - Male 1.27 [0.73–2.21] 0.388 - - Vaccinated (EPI) No ( ref .) - - - - Yes 0.71 [0.30–1.68] 0.427 - - Other cases in HH No ( ref .) - - - - Yes 0.70 [0.34–1.42] 0.312 - - Sought care No ( ref .) - - - - Yes 3.90 [0.81–18.87] 0.175 - - 1 RR = Risk Ratio, CI = Confidence Interval, HH = Household Extrapolating the AR to the population of Yakusu HZ, the total number of cases was estimated at 22,068 (95% CI 18,980 − 25,553) overall and 14,057 (95% CI 12,194 − 15,960) among children aged under 5 years, suggesting the surveillance system detected just 27.9% [95% CI 32.4–24.1] of cases overall, and 34.7% [95% CI 40.0-30.5] among children aged under 5 years. The estimated number of deaths in Yakusu HZ was 1016 (95% CI 665–1458) overall and 919 [95% CI 604–1295] among children aged under 5, suggesting an even lower proportion of detection for deaths of 15.0% [95% CI 22.8–10.4] (overall) and 15.1% [95% CI 23.0-10.7] (under 5). Measles vaccination coverage Just over two-thirds of the general population (2617/3855, 67.9% [95%CI 62.2–73.6]) reported having been vaccinated through routine EPI, and a similar proportion of the target age group reported being vaccinated during the MVC (1079/1594, 67.7% [95%CI 61.6–73.8]), among whom only 116 (7.28% [95%CI 4.08–10.5]) could be verified by card. The proportion of the target age group vaccinated either during EPI or MVC (or both) was only marginally higher (1280/1560, 82.1% [95%CI 78.0-86.1]). Just over half of the target age group reported being vaccinated during both EPI and MVC (819/1530, 53.5% [95%CI 46.8–60.3]). Geospatial analyses There was a high degree of spatial overlap in vaccination coverage by EPI and SIA among children aged under 5 years, with pockets of low coverage in the west and centre of the HZ (Fig. 3 ). While prior to the MVC, the AR was greatest in the peripheral areas of the HZ, in phase 3, following the termination of MVC, the spatial distribution of the IR was approximately the inverse of the vaccination coverage, i.e. in those areas with lowest vaccination coverage (Fig. 3 ). Discussion In our study, we have described key aspects of a large, deadly outbreak of measles in Yakusu HZ, DRC. We found extremely high community ARs among the under-5s compared to previously reported measles epidemics in DRC and other sub-Saharan African countries [ 15 , 6 , 16 – 20 ]. Roughly two-thirds of cases occurred among under 5s, with an AR nearing 50% among this age group. Measles was the main cause of death for under 5s, with a high CFR that was much higher than that reported in routine data, and similar to that previously reported in neighbouring Aketi HZ [ 21 ]. Among under 1s, the situation was worse, with measles killing roughly one in seven infants with this disease. We also documented elevated measles-related mortality for longer than the standard one-month period used to define a measles death, with measles killing nearly one-quarter of infants with this disease. We found that the routine surveillance system showed poor sensitivity for detecting measles cases, detecting approximately one-quarter of all cases and one-third of cases under 5. Sensitivity was lower for detecting deaths, a previously documented finding which is due to poor documenting of measles deaths, as deaths often result from complications with what can be substantial delay following disease onset, by which time the typical measles signs and symptoms may have resolved. As surveillance system strengthening is essential to meet measles elimination standards [ 22 ], it is important to invest in reinforcing both routine surveillance and Early Warning, Alert and Response Systems (EWARS), in this context [ 23 , 24 ]. Being vaccinated during EPI or the MVC was protective against measles disease. Both routine and campaign coverage were low, at around two-thirds of the target population, while the total proportion of children vaccinated by either was only around 80%, substantially below the target of 95% coverage of two doses necessary to interrupt transmission [ 22 , 25 ]. This finding, combined with the geospatial analyses showing a high degree of spatial overlap between EPI and MVC coverage, suggests that the campaign mostly reached the same children in the same areas as EPI, as has been previously reported [ 26 ]. Furthermore, reported measles vaccination status is an unreliable predictor of seroprotection [ 27 , 28 ]. The implication is that there are pockets of under-reached children in Yakusu HZ, particularly among more remote populations, resulting in the outbreak perpetuating in those areas of both low EPI and MVC coverage. In addition, while the MVC was shown to have an impact on individual-level measles infection, it was implemented more than one year after the outbreak started, and the impact on the overall outbreak is less clear. The campaign could arguably have been implemented much earlier, and had it been, many cases and deaths might have been averted. Limitations As this was a retrospective household survey, reported cases and causes of death were not clinically confirmed. To mitigate this, surveyors used a measles community case definition including images of the maculopapular blanching rash. Reported vaccination status may be subject to recall bias; this was mitigated by the attempt to verify reported status by documentary evidence, however, as vaccination cards were not systematically distributed during the MVC, very few could be verified in this way. Due to the long recall period, recall bias may also have affected the reporting of deaths, particularly those that occurred earlier in the outbreak. As some communities within the target area were inaccessible due to security and/or logistical reasons, it is likely that the results described were underestimates of the true impact of the epidemic, as such communities are typically worse affected due to poor access to healthcare. Conclusion Yakusu Health Zone was affected by a high-impact measles epidemic which was characterised by both very high attack rates and case fatality ratio, particularly among under 5s, with mortality concentrated among the under 1s. Important contributing factors were poor routine vaccination coverage and delayed reactive vaccination, which, when it was finally implemented, mostly reached those already vaccinated, with the epidemic continuing to propagate in under-vaccinated locations. Declarations Availability of data and materials statement The minimal dataset underlying the findings of this study is available on request, in accordance with the legal framework set forth by Médecins Sans Frontières (MSF) data sharing policy [29]. MSF is committed to share and disseminate health data from its programs and research in an open, timely, and transparent manner in order to promote health benefits for populations while respecting ethical and legal obligations towards patients, research participants, and their communities. The MSF data sharing policy ensures that data will be available upon request to interested researchers while addressing all security, legal, and ethical concerns. All readers may contact the generic address [email protected] or Ms. Aminata Ndiaye ( [email protected] ) to request data. Competing interests The authors declare that they have no competing interests. Funding This study was funded by Médecins Sans Frontières (MSF). MSF authors were involved in study conceptualization and design, data collection, analysis, and manuscript preparation. The funder had no additional role in the decision to publish. Acknowledgments We thank the population of Yakusu for participating in the study, the health staff of Yakusu HZ for their involvement in the survey and Médecins Sans Frontières teams in the field and at headquarters for their support and advice. Author Contributions Conceptualization: Etienne Gignoux, Iza Ciglenecki, Franck Ale Formal analysis: Etienne Gignoux, Jonathan Polonsky, M. Eugenia Riccio Investigation: Franck Ale, Yves Katuala, Théophile Maloko, Georges Tonamou Methodology: Etienne Gignoux, Jonathan Polonsky, Iza Ciglenecki, M. 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Generic protocol for determining measles case fatality rates in a community, either during an epidemic or in a highly endemic area Baddeley A, Turner R, Rubak E (2023) spatstat: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests Nadaraya (2012) Nonparametric Estimation of Probability Densities and Regression Curves. Springer Science & Business Media R Core Team (2023) R: A language and environment for statistical computing Council for International Organizations of Medical Sciences (2002) International ethical guidelines for biomedical research involving human subjects. Bull Med Ethics. ;:17–23 Council for international organizations of medical sciences International Ethical Guidelines for Epidemiological Studies Grais RF, Dubray C, Gerstl S, Guthmann JP, Djibo A, Nargaye KD et al (2007) Unacceptably high mortality related to measles epidemics in Niger, Nigeria, and Chad. PLoS Med 4:e16 Minetti A, Bopp C, Fermon F, François G, Grais RF, Grout L et al (2013) Measles Outbreak Response Immunization Is Context-Specific: Insight from the Recent Experience of Médecins Sans Frontières. PLOS Med 10:e1001544 Minetti A, Kagoli M, Katsulukuta A, Huerga H, Featherstone A, Chiotcha H et al (2013) Lessons and Challenges for Measles Control from Unexpected Large Outbreak, Malawi. Emerg Infect Dis 19:202–209 Mancini S, Coldiron ME, Ronsse A, Ilunga BK, Porten K, Grais RF (2014) Description of a large measles epidemic in Democratic Republic of Congo, 2010–2013. Confl Health 8:9 Polonsky JA, Singh B, Masiku C, Langendorf C, Kagoli M, Hurtado N et al (2015) Exploring HIV infection and susceptibility to measles among older children and adults in Malawi: a facility-based study. Int J Infect Dis 31:61–67 Coulborn RM, Nackers F, Bachy C, Porten K, Vochten H, Ndele E et al (2020) Field challenges to measles elimination in the Democratic Republic of the Congo. Vaccine 38:2800–2807 Gignoux E, Polonsky J, Ciglenecki I, Bichet M, Coldiron M, Lwiyo ET et al (2018) Risk factors for measles mortality and the importance of decentralized case management during an unusually large measles epidemic in eastern Democratic Republic of Congo in 2013. PLoS ONE 13:e0194276 World Health Organization (2020) Measles and rubella strategic framework: 2021–2030. World Health Organization Keita M, Lucaccioni H, Ilumbulumbu MK, Polonsky J, Nsio-Mbeta J, Panda GT et al (2021) Evaluation of Early Warning, Alert and Response System for Ebola Virus Disease, Democratic Republic of the Congo, 2018–2020. Emerg Infect Dis 27:2988–2998 Keita M, Talisuna A, Chamla D, Burmen B, Cherif MS, Polonsky JA et al (2023) Investing in preparedness for rapid detection and control of epidemics: analysis of health system reforms and their effect on 2021 Ebola virus disease epidemic response in Guinea. BMJ Glob Health 8:e010984 Gastañaduy PA, Goodson JL, Panagiotakopoulos L, Rota PA, Orenstein WA, Patel M (2021) Measles in the 21st Century: Progress Toward Achieving and Sustaining Elimination. J Infect Dis 224(12 Suppl 2):S420–S428 Garly ML, Martins CL, Balé C, da Costa F, Dias F, Whittle H et al (1999) Early two-dose measles vaccination schedule in Guinea-Bissau: good protection and coverage in infancy. Int J Epidemiol 28:347–352 Polonsky JA, Juan-Giner A, Hurtado N, Masiku C, Kagoli M, Grais RF (2015) Measles seroprevalence in Chiradzulu district, Malawi: Implications for evaluating vaccine coverage. Vaccine 33:4554–4558 Katanyutanon A, Thanasopon W, Sonthichai C, Angsuwatcharakorn P, Chansaenroj J, Nakabut R et al Seroprevalence of measles and varicella in healthcare workers in Chonburi province, Thailand between October 2022 and January 2023. 2024;:2024.02.18.24303008. Karunakara U (2013) Data sharing in a humanitarian organization: the experience of Médecins Sans Frontières. PLoS Med 10:e1001562 Additional Declarations The authors declare no competing interests. Supplementary Files Appendix.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6878790","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":470272741,"identity":"d2ab6c92-7882-4e2f-878d-1e8af7fca74e","order_by":0,"name":"Franck Alé","email":"","orcid":"","institution":"Médecins Sans Frontières, Abidjan, Côte d’Ivoire","correspondingAuthor":false,"prefix":"","firstName":"Franck","middleName":"","lastName":"Alé","suffix":""},{"id":470272742,"identity":"51ec729a-a9f2-4d6c-a090-73c573454e5a","order_by":1,"name":"M. Eugenia Riccio","email":"","orcid":"","institution":"Médecins Sans Frontières, Geneva, Switzerland","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"Eugenia","lastName":"Riccio","suffix":""},{"id":470272743,"identity":"b57ebfdc-ce82-43fd-b825-8c9ce5948285","order_by":2,"name":"Yves Katuala","email":"","orcid":"","institution":"Médecins Sans Frontières, Abidjan, Côte d’Ivoire","correspondingAuthor":false,"prefix":"","firstName":"Yves","middleName":"","lastName":"Katuala","suffix":""},{"id":470272744,"identity":"38327743-10c4-4578-9762-b494845bd11a","order_by":3,"name":"Théophile Maloko","email":"","orcid":"","institution":"Ministry of Public Health, Tshopo, Democratic Republic of the Congo","correspondingAuthor":false,"prefix":"","firstName":"Théophile","middleName":"","lastName":"Maloko","suffix":""},{"id":470272745,"identity":"4380d7eb-ce9f-4c29-858f-52eac8a0d7cd","order_by":4,"name":"Georges Tonamou","email":"","orcid":"","institution":"Médecins Sans Frontières, Kinshasa, Democratic Republic of the Congo","correspondingAuthor":false,"prefix":"","firstName":"Georges","middleName":"","lastName":"Tonamou","suffix":""},{"id":470272746,"identity":"d112881f-6d17-4be4-9552-79ccff3d8601","order_by":5,"name":"Etienne Gignoux","email":"","orcid":"","institution":"Epicentre, Paris, France","correspondingAuthor":false,"prefix":"","firstName":"Etienne","middleName":"","lastName":"Gignoux","suffix":""},{"id":470272747,"identity":"556fb339-e07e-41c9-82f4-a93b6dc7e67c","order_by":6,"name":"Iza Ciglenecki","email":"","orcid":"","institution":"Médecins Sans Frontières, Geneva, Switzerland","correspondingAuthor":false,"prefix":"","firstName":"Iza","middleName":"","lastName":"Ciglenecki","suffix":""},{"id":470272748,"identity":"433dcea6-f9ed-4482-b13d-79c9fb52c4e2","order_by":7,"name":"Jonathan Polonsky","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABYElEQVRIie3RPUvDQBgH8KsHl+VscLsQaL/CQaE6SP0qOQLnci1CF8VSM12XWNe6+BmcxDHhIFniy9gxpdC5RZAOBb20FWNpnQXzHx4SuN89d88BUKTIH4zh6VLKSlVFYCa77D7Wf873isomWa4Os0I4L91GyqVJsCJ4taL2CxF1uD8JuDVYt9hJetfh2+yx0foiwrTGUZp2jlsntgr2hgsKTDt+zRP/2SVh4rZBNdHkoXuObH5KnYi3cZk7sCkpsPriLE8GgpJQQuYRnBGoiagT5inmY0xh01sAmmDnJ6nNQ3m1JndQIOvlXZMPTcwpFPpgG+RgoPcMpVqTPuSIYKRJkHUBeoeMGEGO2DipHz3JmEmC9JD7ykWYH+q7uMxPEFX6LtjycX5iZcOvDS/kJbshMJ5mTykNNRnNOw3W8+ForA9WMbGRbk46C9r6HazeB9NtZBdfZnuXIkWKFPkv+QTHMH5qUkn6lwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-8634-4255","institution":"Epicentre, Paris, France","correspondingAuthor":true,"prefix":"","firstName":"Jonathan","middleName":"","lastName":"Polonsky","suffix":""}],"badges":[],"createdAt":"2025-06-12 09:25:20","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6878790/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6878790/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84677359,"identity":"e55b74d4-9020-4c69-b95d-756a52c98bc0","added_by":"auto","created_at":"2025-06-16 07:53:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30284,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eEpidemic curve showing\u003c/em\u003e \u003cem\u003ereported\u003c/em\u003e \u003cem\u003emeasles cases by month, detected by routine surveillance, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018 – 30 June 2019. Orange bar shows the period during which MSF offered free healthcare to all suspected measles cases (3 Mar – 20 Apr 2019); blue bar shows the period during which supplemental immunization activities were conducted (7 – 20 Apr 2019).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6878790/v1/6ef99183789f1120c994120a.png"},{"id":84678779,"identity":"c10b52ef-1b18-4ab2-a7d6-b53154daacab","added_by":"auto","created_at":"2025-06-16 08:01:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":31733,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eEpidemic curve showing\u003c/em\u003e \u003cem\u003emeasles cases by month, as reported during retrospective survey, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018 – 30 June 2019. Cases detected in July 2019 are not represented in the graph as the cases were only collected until the 9th of this month, last day of the survey\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6878790/v1/5307dce29b14de6ce55e87e0.png"},{"id":84677364,"identity":"2b33f276-8693-482a-abca-9f597f97ab58","added_by":"auto","created_at":"2025-06-16 07:53:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":188659,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eGeospatial distribution of the proportion of children aged under 5 years having received measles vaccine dose during (a) routine delivery and (b) mass reactive vaccination campaign, and of the measles attack rate (c) before and (d) after the campaign, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018 – 30 June 2019.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6878790/v1/c8c9b00b67305385d977d272.png"},{"id":84679772,"identity":"84adbf21-a0de-4626-91e6-bca6508155b1","added_by":"auto","created_at":"2025-06-16 08:09:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1145421,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6878790/v1/c8c332ec-7a01-4b8f-a1f3-5b8654cf18f6.pdf"},{"id":84677356,"identity":"56faddbb-3378-4bc3-88dd-aad07bdf2a6c","added_by":"auto","created_at":"2025-06-16 07:53:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14391,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-6878790/v1/36331d19ca24f32f7ceee137.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDescription of a large and deadly measles epidemic, Yakusu health zone, Democratic Republic of Congo, 2018-2019: A retrospective study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMeasles was historically a major contributor to child morbidity and mortality globally prior to the widespread implementation of a highly effective vaccine [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Following enormous progress in measles elimination in the latter years of the 20th century, measles incidence continued to decrease considerably in the 21st century, from 145 to 17 cases per million people between 2000 and 2021 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This progress was accompanied by a concomitant decline in annual measles-related deaths, decreasing from an estimated 761,000 to 128,000, averting an estimated 56\u0026nbsp;million deaths [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these achievements, measles epidemics persist, particularly in sub-Saharan Africa [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Due to the combined effects of low vaccination coverage, inadequate surveillance, and a struggling healthcare system, the Democratic Republic of the Congo (DRC) experienced between 2018\u0026ndash;2019 one of the largest measles outbreaks ever recorded, with 311,471 reported cases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. M\u0026eacute;decins Sans Fronti\u0026egrave;res (MSF), in collaboration with the DRC Ministry of Public Health (MoH), responded to this crisis by reinforcing surveillance, providing free medical care, and conducting vaccination campaigns.\u003c/p\u003e \u003cp\u003eYakusu Health Zone (HZ), Tshopo province, was one the most affected areas. Out of an estimated population of 142,379, 6,150 measles cases (attack rate [AR]: 4.3%) and 152 measles-attributable deaths (case fatality ratio [CFR]: 2.5%) were reported between Jan 1 2018 and 30 June 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring the peak of the epidemic, between 3 March and 20 April 2019, MSF supported the MoH by providing free treatment to a total of 2,615 patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, between 7\u0026ndash;20 April, MoH conducted a mass vaccination campaign (MVC) targeting all children aged 6\u0026ndash;59 months.\u003c/p\u003e \u003cp\u003eDue to limited access to healthcare, weak disease surveillance systems, and incomplete health records leading to under-attribution of measles as cause of death [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], the reported AR and CFR were likely substantially underestimated. Therefore, this study aims to document the impact of the outbreak by estimating several key parameters for both the overall population and among children aged under 5 years (under-5s) specifically: the AR; CFR; measles-specific proportional mortality (MSPM); and the daily crude and under-5 mortality rates (CMR and U5MR, respectively).\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis was a cross-sectional two-stage cluster survey, conducted in Yakusu HZ from 2\u0026ndash;9 July 2019. The target population was any person residing for at least four weeks in Yakusu HZ during the recall period (from 1 January 2018 until the date of data collection).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSampling method\u003c/h3\u003e\n\u003cp\u003eHouseholds were chosen using two-stage cluster sampling as recommend by WHO [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. At the first stage, 40 clusters were selected with a probability proportional to the size of the village or quarter from which the cluster was selected. At the second stage, 25 households were selected by randomly generating GPS points within the perimeter of the village or quarter from which the cluster was selected. When the perimeter of the village or quarter was unknown or incorrect, a systematic random sample was included instead. In villages where there were fewer than 25 households, all households were selected for inclusion. Tablets provided to each surveyor team were equipped with OsmAnd (OSM Automated Navigation Directions) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] software to identify the household closest to each randomly generated GPS points in order to start household selection within each cluster. Subsequent households were selected based on proximity to the prior household using a defined protocol.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eInformation was collected on demographic characteristics, measles vaccination and infection status, and, where appropriate, access to healthcare and cause of death, for all individuals (Supplementary information).\u003c/p\u003e \u003cp\u003eSurveyors underwent a 3-day training on household selection, obtaining informed consent, and conducting the survey through practical work and role play. A pilot study was conducted outside of the survey target area to test and adapt the survey material to the local context. Interviews were conducted in Lingala or Swahili, the local languages.\u003c/p\u003e \u003cp\u003eCommunity leaders and heads of households were informed about the survey several days before the planned site visits and the interview date was arranged with those household respondents willing to participate. On the interview date, eight teams comprising two surveyors each visited the selected households, explained the survey objectives to the primary respondent, and obtained informed consent to participate. If consent was provided, all household members were included in the survey. Participation refusals were recorded in logbooks. Data were collected on mobile devices using KoBoCollect software [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMain definitions\u003c/h3\u003e\n\u003cp\u003eA measles case was defined as any individual with the following symptoms: maculopapular rash during at least 3 days, \u0026ge;\u0026thinsp;38\u0026deg;C fever (or warm to the touch), and cough or upper respiratory tract infection or conjunctivitis. A measles-specific death was defined as any death occurring within 31 days of onset of measles symptoms [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. As there is increasing evidence that elevated measles mortality may persist for longer than this, we also performed a sensitivity analysis for mortality over an extended period, using an alternative definition for a measles-specific death as any death occurring within 90 days of onset of measles symptoms.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eMeasles IR was calculated as the number of cases divided by the average person-time at-risk during one year, expressed as cases per 1000 person-years. Measles AR was calculated as the number of measles cases divided by the number of persons included in the survey during the recall period. CFR was calculated as the number of measles-specific deaths divided by the number of measles cases. MSPM was calculated as the number of measles-attributable deaths divided by the total number of deaths recorded. AR, CFR, and MSPM were expressed as percentages.\u003c/p\u003e \u003cp\u003eAll-cause and measles-specific mortality rates, expressed as deaths per 10,000 person-days, were estimated as the number of (measles-specific) deaths divided by the total person-time at risk multiplied by 10,000. Person-time at risk depended on time spent in the household: for the majority of participants who spent the entire recall period as household members, the exposure period was calculated as the whole recall period; for participants who migrated in or out of the household during the recall period, the exposure period was calculated as half the total recall period; and finally, for any participants who were born and/or died during the recall period, the exposure period was calculated taking these dates into consideration.\u003c/p\u003e \u003cp\u003eAll analyses were performed for all individuals and separately for children aged under 5 years, who represent the segment of the population most vulnerable to measles and were therefore the target of the reactive vaccination campaign. Additionally, stratified analyses were performed according to three periods, to evaluate the impact of MSF intervention: the period prior to the MSF interventions (Phase 1; 1 Jan 2018\u0026ndash;2 March 2019), the period covering the MSF interventions (Phase 2; 3 March \u0026ndash; 20 April 2019), and the period between the cessation of MSF\u0026rsquo;s activities and the survey date (Phase 3; 21 April \u0026ndash; 30 June 2019).\u003c/p\u003e \u003cp\u003eTo describe the risk factors associated with measles mortality, we fitted a log Poisson regression model and used a multilevel model including random effects at cluster and household levels. We included sex, age group, period of onset, and EPI vaccination status as explanatory variables. In the univariate analysis, all variables were tested for association with measles mortality, and those with p\u0026thinsp;\u0026lt;\u0026thinsp;0.1 were included in the multivariate analysis.\u003c/p\u003e \u003cp\u003eTo estimate the population-level impact of the outbreak and the proportion of cases and deaths detected by the surveillance system (calculated as the number of cases detected divided by the estimated total number of cases), estimates of the true number of cases and measles-specific deaths within Yakusu HZ were calculated by extrapolation of survey results to the estimated population size.\u003c/p\u003e \u003cp\u003eMeasles vaccination coverage was estimated as the proportion of individuals reporting having received any dose of the vaccine (either by vaccination card or by parental recall). Coverage was estimated separately for both the routine Expanded Program on Immunization (EPI) which targets children aged 9\u0026ndash;11 months, and the Supplementary Immunization Activity (SIA) campaign which targeted children aged 6\u0026ndash;59 months.\u003c/p\u003e \u003cp\u003eGeospatial analyses were conducted to show spatial distributions of i) EPI and reactive mass campaign coverage, and ii) measles AR, among children aged 6\u0026ndash;59 months (the age group targeted for vaccination). Point pattern datasets were created using the R package \u0026ldquo;Spatstat\u0026rdquo; [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], applying cluster-specific estimates of vaccination coverage and AR to the geographic coordinates of each cluster. These data were smoothed using a Gaussian kernel function, and visualized in heat maps [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll data were analyzed using R statistical software [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEthics\u003c/h2\u003e \u003cp\u003e The study protocol was approved by the MSF Ethics Review Board and the Research Ethics Committee of Kisangani University, DRC. The survey was conducted in accordance with the international ethics guidelines for biomedical research involving human subjects and the guidelines for the conduct of epidemiological studies of the Council for International Organization of Medical Science (CIOMS) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVarious community authorities (including village and religious chiefs and heads of households) were informed of the survey objectives and received a copy of the information sheet in their local language. Verbal consent from the head-of-household was mandatory to participate in the survey. It was clearly stated that all participants were free to withdraw from the study at any time without any consequence. Confidentiality was maintained during the interviewing process.\u003c/p\u003e \u003cp\u003eAll collected data were pseudo-anonymized (with only first names collected), and electronic files were stored on a password-protected remote server, to which only investigators had access.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSample description\u003c/h2\u003e \u003cp\u003eA total of 1,101 households were selected for participation in the survey, of which 1,080 (98.1%), comprising 8,968 individuals, consented to participate. The mean household size was 9.1 (95% confidence interval [CI]: 8.6\u0026ndash;9.5), and the median age was 14 (IQR 5\u0026ndash;28), with approximately one-fifth (21.6% [95%CI 20.6\u0026ndash;22.5]) of the population aged under 5 years. The male-to-female sex ratio was 1.01 (0.96\u0026ndash;1.06).\u003c/p\u003e \u003cp\u003eOver three-quarters of the participants (6,905, 77.0%) were present in the household throughout the entire recall period, while 496 (5.5%) joined and 657 (7.3%) left the household during the recall period. There were 724 births and 313 deaths during the recall period (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). At the time of the survey, 7,998 individuals (89.2%) were current members of the household. Approximately half (4566, 50.9%) of study participants were aged under 15 years, while there was an even split between males (4505, 50.2%) and females (4463, 49.8%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDescription of study participants by characteristics, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018\u0026ndash;30 June 2019.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;1 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e400 (4.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1534 (17.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1563 (17.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;14 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1069 (11.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4402 (49.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4463 (49.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4505 (50.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVaccination (EPI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot vaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1238 (13.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2617 (29.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5113 (57.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVaccination (MVC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot vaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e641 (7.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1338 (14.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6989 (77.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVaccination (EPI \u0026amp;/or MVC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot vaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e341 (3.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2929 (32.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5698 (63.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMeasles case\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-case\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7578 (84.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1390 (155.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStatus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8655 (96.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e313 (3.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8968 (100)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMeasles cases\u003c/h2\u003e \u003cp\u003eAfter having the standard measles case definition explained to participants, there were 1,390 self-reported cases (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with a temporal distribution that closely matched that described by the routine surveillance data (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This yielded respective overall and under 5 ARs of 15.5% [95%CI 13.2\u0026ndash;17.8] and 45.7% [95% CI 39.6\u0026ndash;51.9] (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a multivariate analysis, children aged under 5 years had a much higher risk of becoming a case (Risk Ratio [RR] 2.5 [95%CI 2.1\u0026ndash;2.9]), while individuals who had received vaccine either by routine EPI or campaign had a significantly lower risk (RR 0.80 [95%CI 0.68\u0026ndash;0.93]).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDescription of measles cases and decedents, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018\u0026ndash;30 June 2019.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCases (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeaths (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;1 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (31.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e807 (58.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (58.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e416 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (8.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;14 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (-)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e691 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (43.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e699 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (56.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccination (EPI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot vaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e385 (27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (29.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e824 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (39.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e181 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (31.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther cases in HH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e215 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (20.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1175 (84.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (79.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSought care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e287 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1103 (79.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (93.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1390 (100)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e48 (100)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eCases, deaths, CFR, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018\u0026ndash;30 June 2019.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCases\u003c/p\u003e \u003cp\u003e(AR% [95%CI])\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDeaths (31-days)\u003c/p\u003e \u003cp\u003e(CFR% [95%CI])\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDeaths (90-days)\u003c/p\u003e \u003cp\u003e(CFR% [95%CI])\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;1 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (19.2 [15.0-23.5])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (19.5 [12.1\u0026ndash;26.9])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (23.4 [12.9\u0026ndash;33.8])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e807 (52.6 [45.2\u0026ndash;60.0])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (3.5 [2.0-4.9])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38 (4.7 [3.3\u0026ndash;6.2])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e416 (26.6 [21.6\u0026ndash;31.6])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.0 [0.0-1.9])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (1.2 [0.1\u0026ndash;2.3])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;14 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (5.3 [3.6-7.0])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (-)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (-)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (0.8 [0.5-1.0])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3.0 [-2.6-8.6])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (3.0 [-2.68.6])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClassical age groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e884 (45.7 [39.6\u0026ndash;51.9])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (4.9 [3.4\u0026ndash;6.3])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56 (6.3 [4.7\u0026ndash;7.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e506 (7.2 [5.8\u0026ndash;8.5])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1.0 [0.1\u0026ndash;1.8])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (1.2 [0.3\u0026ndash;2.1])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e691 (15.5 [13.2\u0026ndash;17.8])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (2.5 [1.4\u0026ndash;3.6])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (3.5 [2.2\u0026ndash;4.8])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e699 (15.5 [12.9\u0026ndash;18.1])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (2.6 [1.4\u0026ndash;3.7])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38 (5.4 [3.6\u0026ndash;7.2])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1390 (15.5 [13.2\u0026ndash;17.8])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (2.5 [1.7\u0026ndash;3.4])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 (4.5 [3.4\u0026ndash;5.5])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMortality\u003c/h2\u003e \u003cp\u003eCFR up to 31 days post-onset of symptoms was 3.5% [95% CI 2.5\u0026ndash;4.5] overall (48 deaths among 1,390 cases), 4.9% [95% CI 3.4\u0026ndash;6.3];) among under 5s (43/884), and 19.5% [95% CI 12.1\u0026ndash;26.9]) among under 1s (15/77). However, for deaths within 90 days post-onset, this increased to 4.5% [95%CI 3.38\u0026ndash;5.54] (62/1390) overall, 6.3% [95%CI 4.7\u0026ndash;7.9] (56/884) among under 5s, and 23.4% [95%CI 12.9\u0026ndash;33.8] (18/77) among under 1s.\u003c/p\u003e \u003cp\u003eCMR was 0.72 per 10,000 person-days (95% CI 0.62\u0026ndash;0.82), while U5MR was 1.51 per 10,000 person-days ([95% CI 1.19\u0026ndash;1.84]). Among 313 reported deaths, 48 (15.3% [95%CI 10.9\u0026ndash;19.8]) were attributable to measles, and among under 5s, this number was 43 (35.2% [95%CI 26.0-44.5]) of 122 deaths. 90-day all-cause CMR was 0.96 per 10,000 person-days (95%CI 0.71\u0026ndash;1.20) for measles patients, compared to 0.66 per 10,000 person-days (95%CI 0.56\u0026ndash;0.76) for non-cases (rate difference\u0026thinsp;=\u0026thinsp;0.30 [95%CI 0.03\u0026ndash;0.56], p\u0026thinsp;=\u0026thinsp;0.028). 90-day all-cause U5MR was 1.46 per 10,000 person-days (95%CI 1.06\u0026ndash;1.85) for measles patients, compared to 1.47 per 10,000 person-days (95%CI 1.05\u0026ndash;1.89) for non-cases (rate difference = -0.02 [95%CI -0.59-0.56], p\u0026thinsp;=\u0026thinsp;0.949).\u003c/p\u003e \u003cp\u003eMSPM was 15.3% [95%CI 10.9\u0026ndash;19.8] overall, 35.2% [95%CI 26.0-44.5] among the under 5s, and 27.3% [95%CI 19.5\u0026ndash;35.0] among the under 1s.\u003c/p\u003e \u003cp\u003eIn the univariate analysis, age group was the only covariate associated with risk of dying from measles; children aged 1\u0026ndash;4 years had one eighth the risk of dying from measles compared to under 1s (RR 0.12 [95%CI 0.06\u0026ndash;0.28]), while this risk was twenty times lower among individuals aged 5 years and older (RR 0.05 [95%CI 0.02\u0026ndash;0.15]) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eMultivariable Poisson regression of risk factors for mortality among measles cases, Yakusu Health Zone, Tshopo Province, Democratic Republic of the Congo, 1 January 2018\u0026ndash;20 April 2019.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRR [95%CI]\u003c/b\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRR [95%CI]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;1 years (\u003cem\u003eref.\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12 [0.06\u0026ndash;0.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 [0.06\u0026ndash;0.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05 [0.02\u0026ndash;0.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05 [0.02\u0026ndash;0.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (\u003cem\u003eref.\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27 [0.73\u0026ndash;2.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccinated (EPI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo (\u003cem\u003eref\u003c/em\u003e.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.71 [0.30\u0026ndash;1.68]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther cases in HH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo (\u003cem\u003eref\u003c/em\u003e.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.70 [0.34\u0026ndash;1.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSought care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo (\u003cem\u003eref\u003c/em\u003e.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.90 [0.81\u0026ndash;18.87]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e RR\u0026thinsp;=\u0026thinsp;Risk Ratio, CI\u0026thinsp;=\u0026thinsp;Confidence Interval, HH\u0026thinsp;=\u0026thinsp;Household\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eExtrapolating the AR to the population of Yakusu HZ, the total number of cases was estimated at 22,068 (95% CI 18,980\u0026thinsp;\u0026minus;\u0026thinsp;25,553) overall and 14,057 (95% CI 12,194\u0026thinsp;\u0026minus;\u0026thinsp;15,960) among children aged under 5 years, suggesting the surveillance system detected just 27.9% [95% CI 32.4\u0026ndash;24.1] of cases overall, and 34.7% [95% CI 40.0-30.5] among children aged under 5 years. The estimated number of deaths in Yakusu HZ was 1016 (95% CI 665\u0026ndash;1458) overall and 919 [95% CI 604\u0026ndash;1295] among children aged under 5, suggesting an even lower proportion of detection for deaths of 15.0% [95% CI 22.8\u0026ndash;10.4] (overall) and 15.1% [95% CI 23.0-10.7] (under 5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMeasles vaccination coverage\u003c/h2\u003e \u003cp\u003eJust over two-thirds of the general population (2617/3855, 67.9% [95%CI 62.2\u0026ndash;73.6]) reported having been vaccinated through routine EPI, and a similar proportion of the target age group reported being vaccinated during the MVC (1079/1594, 67.7% [95%CI 61.6\u0026ndash;73.8]), among whom only 116 (7.28% [95%CI 4.08\u0026ndash;10.5]) could be verified by card. The proportion of the target age group vaccinated either during EPI or MVC (or both) was only marginally higher (1280/1560, 82.1% [95%CI 78.0-86.1]). Just over half of the target age group reported being vaccinated during both EPI and MVC (819/1530, 53.5% [95%CI 46.8\u0026ndash;60.3]).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGeospatial analyses\u003c/h2\u003e \u003cp\u003eThere was a high degree of spatial overlap in vaccination coverage by EPI and SIA among children aged under 5 years, with pockets of low coverage in the west and centre of the HZ (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). While prior to the MVC, the AR was greatest in the peripheral areas of the HZ, in phase 3, following the termination of MVC, the spatial distribution of the IR was approximately the inverse of the vaccination coverage, i.e. in those areas with lowest vaccination coverage (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study, we have described key aspects of a large, deadly outbreak of measles in Yakusu HZ, DRC. We found extremely high community ARs among the under-5s compared to previously reported measles epidemics in DRC and other sub-Saharan African countries [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17 CR18 CR19\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Roughly two-thirds of cases occurred among under 5s, with an AR nearing 50% among this age group. Measles was the main cause of death for under 5s, with a high CFR that was much higher than that reported in routine data, and similar to that previously reported in neighbouring Aketi HZ [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Among under 1s, the situation was worse, with measles killing roughly one in seven infants with this disease. We also documented elevated measles-related mortality for longer than the standard one-month period used to define a measles death, with measles killing nearly one-quarter of infants with this disease.\u003c/p\u003e \u003cp\u003eWe found that the routine surveillance system showed poor sensitivity for detecting measles cases, detecting approximately one-quarter of all cases and one-third of cases under 5. Sensitivity was lower for detecting deaths, a previously documented finding which is due to poor documenting of measles deaths, as deaths often result from complications with what can be substantial delay following disease onset, by which time the typical measles signs and symptoms may have resolved. As surveillance system strengthening is essential to meet measles elimination standards [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], it is important to invest in reinforcing both routine surveillance and Early Warning, Alert and Response Systems (EWARS), in this context [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeing vaccinated during EPI or the MVC was protective against measles disease. Both routine and campaign coverage were low, at around two-thirds of the target population, while the total proportion of children vaccinated by either was only around 80%, substantially below the target of 95% coverage of two doses necessary to interrupt transmission [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This finding, combined with the geospatial analyses showing a high degree of spatial overlap between EPI and MVC coverage, suggests that the campaign mostly reached the same children in the same areas as EPI, as has been previously reported [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, reported measles vaccination status is an unreliable predictor of seroprotection [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The implication is that there are pockets of under-reached children in Yakusu HZ, particularly among more remote populations, resulting in the outbreak perpetuating in those areas of both low EPI and MVC coverage. In addition, while the MVC was shown to have an impact on individual-level measles infection, it was implemented more than one year after the outbreak started, and the impact on the overall outbreak is less clear. The campaign could arguably have been implemented much earlier, and had it been, many cases and deaths might have been averted.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eAs this was a retrospective household survey, reported cases and causes of death were not clinically confirmed. To mitigate this, surveyors used a measles community case definition including images of the maculopapular blanching rash. Reported vaccination status may be subject to recall bias; this was mitigated by the attempt to verify reported status by documentary evidence, however, as vaccination cards were not systematically distributed during the MVC, very few could be verified in this way. Due to the long recall period, recall bias may also have affected the reporting of deaths, particularly those that occurred earlier in the outbreak. As some communities within the target area were inaccessible due to security and/or logistical reasons, it is likely that the results described were underestimates of the true impact of the epidemic, as such communities are typically worse affected due to poor access to healthcare.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eYakusu Health Zone was affected by a high-impact measles epidemic which was characterised by both very high attack rates and case fatality ratio, particularly among under 5s, with mortality concentrated among the under 1s. Important contributing factors were poor routine vaccination coverage and delayed reactive vaccination, which, when it was finally implemented, mostly reached those already vaccinated, with the epidemic continuing to propagate in under-vaccinated locations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe minimal dataset underlying the findings of this study is available on request, in accordance with the legal framework set forth by M\u0026eacute;decins Sans Fronti\u0026egrave;res (MSF) data sharing policy [29]. MSF is committed to share and disseminate health data from its programs and research in an open, timely, and transparent manner in order to promote health benefits for populations while respecting ethical and legal obligations towards patients, research participants, and their communities. The MSF data sharing policy ensures that data will be available upon request to interested researchers while addressing all security, legal, and ethical concerns. All readers may contact the generic address [email protected] or Ms. Aminata Ndiaye ([email protected]) to request data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by M\u0026eacute;decins Sans Fronti\u0026egrave;res (MSF). MSF authors were involved in study conceptualization and design, data collection, analysis, and manuscript preparation. The funder had no additional role in the decision to publish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the population of Yakusu for participating in the study, the health staff of Yakusu HZ for their involvement in the survey and M\u0026eacute;decins Sans Fronti\u0026egrave;res teams in the field and at headquarters for their support and advice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Etienne Gignoux, Iza Ciglenecki, Franck Ale\u003c/p\u003e\n\u003cp\u003eFormal analysis: Etienne Gignoux, Jonathan Polonsky, M. Eugenia Riccio\u003c/p\u003e\n\u003cp\u003eInvestigation: Franck Ale, Yves Katuala, Th\u0026eacute;ophile\u0026nbsp;Maloko, Georges Tonamou\u003c/p\u003e\n\u003cp\u003eMethodology: Etienne Gignoux, Jonathan Polonsky, Iza Ciglenecki, M. Eugenia Riccio\u003c/p\u003e\n\u003cp\u003eProject administration: Franck Ale, Etienne Gignoux\u003c/p\u003e\n\u003cp\u003eVisualization: Jonathan Polonsky, Etienne Gignoux, M. Eugenia Riccio\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; original draft: M. Eugenia Riccio, Jonathan Polonsky, Etienne Gignoux, Iza Ciglenecki \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; review \u0026amp; editing: Franck Ale, M. Eugenia Riccio, Yves Katuala, Th\u0026eacute;ophile Maloko, Georges Tonamou, Etienne Gignoux, Iza Ciglenecki, Jonathan Polonsky\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMoss WJ, Measles (2017) Lancet Lond Engl 390:2490\u0026ndash;2502\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinta AA, Ferrari M, Antoni S, Portnoy A, Sbarra A, Lambert B et al (2022) Progress Toward Regional Measles Elimination - Worldwide, 2000\u0026ndash;2021. MMWR Morb Mortal Wkly Rep 71:1489\u0026ndash;1495\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerrari MJ, Grais RF, Bharti N, Conlan AJK, Bj\u0026oslash;rnstad ON, Wolfson LJ et al (2008) The dynamics of measles in sub-Saharan Africa. Nature 451:679\u0026ndash;684\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDucomble T, Gignoux E (2020) Learning from a massive epidemic: measles in DRC. Lancet Infect Dis 20:542\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eN\u0026rsquo;goran AA, Ilunga N, Coldiron ME, Grais RF, Porten K (2013) Community-based measles mortality surveillance in two districts of Katanga Province, Democratic Republic of Congo. BMC Res Notes 6:537\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrout L, Minetti A, Hurtado N, Fran\u0026ccedil;ois G, Fermon F, Chatelain A et al (2013) Measles in Democratic Republic of Congo: an outbreak description from Katanga, 2010\u0026ndash;2011. 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PLOS Med 10:e1001544\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinetti A, Kagoli M, Katsulukuta A, Huerga H, Featherstone A, Chiotcha H et al (2013) Lessons and Challenges for Measles Control from Unexpected Large Outbreak, Malawi. Emerg Infect Dis 19:202\u0026ndash;209\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMancini S, Coldiron ME, Ronsse A, Ilunga BK, Porten K, Grais RF (2014) Description of a large measles epidemic in Democratic Republic of Congo, 2010\u0026ndash;2013. Confl Health 8:9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolonsky JA, Singh B, Masiku C, Langendorf C, Kagoli M, Hurtado N et al (2015) Exploring HIV infection and susceptibility to measles among older children and adults in Malawi: a facility-based study. Int J Infect Dis 31:61\u0026ndash;67\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoulborn RM, Nackers F, Bachy C, Porten K, Vochten H, Ndele E et al (2020) Field challenges to measles elimination in the Democratic Republic of the Congo. Vaccine 38:2800\u0026ndash;2807\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGignoux E, Polonsky J, Ciglenecki I, Bichet M, Coldiron M, Lwiyo ET et al (2018) Risk factors for measles mortality and the importance of decentralized case management during an unusually large measles epidemic in eastern Democratic Republic of Congo in 2013. PLoS ONE 13:e0194276\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (2020) Measles and rubella strategic framework: 2021\u0026ndash;2030. World Health Organization\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeita M, Lucaccioni H, Ilumbulumbu MK, Polonsky J, Nsio-Mbeta J, Panda GT et al (2021) Evaluation of Early Warning, Alert and Response System for Ebola Virus Disease, Democratic Republic of the Congo, 2018\u0026ndash;2020. Emerg Infect Dis 27:2988\u0026ndash;2998\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeita M, Talisuna A, Chamla D, Burmen B, Cherif MS, Polonsky JA et al (2023) Investing in preparedness for rapid detection and control of epidemics: analysis of health system reforms and their effect on 2021 Ebola virus disease epidemic response in Guinea. BMJ Glob Health 8:e010984\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGasta\u0026ntilde;aduy PA, Goodson JL, Panagiotakopoulos L, Rota PA, Orenstein WA, Patel M (2021) Measles in the 21st Century: Progress Toward Achieving and Sustaining Elimination. J Infect Dis 224(12 Suppl 2):S420\u0026ndash;S428\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarly ML, Martins CL, Bal\u0026eacute; C, da Costa F, Dias F, Whittle H et al (1999) Early two-dose measles vaccination schedule in Guinea-Bissau: good protection and coverage in infancy. Int J Epidemiol 28:347\u0026ndash;352\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolonsky JA, Juan-Giner A, Hurtado N, Masiku C, Kagoli M, Grais RF (2015) Measles seroprevalence in Chiradzulu district, Malawi: Implications for evaluating vaccine coverage. Vaccine 33:4554\u0026ndash;4558\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatanyutanon A, Thanasopon W, Sonthichai C, Angsuwatcharakorn P, Chansaenroj J, Nakabut R et al Seroprevalence of measles and varicella in healthcare workers in Chonburi province, Thailand between October 2022 and January 2023. 2024;:2024.02.18.24303008.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarunakara U (2013) Data sharing in a humanitarian organization: the experience of M\u0026eacute;decins Sans Fronti\u0026egrave;res. PLoS Med 10:e1001562\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Médecins Sans Frontières","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Measles, Disease Outbreaks, Mass Vaccination, Vaccination Coverage, Retrospective Studies, Health Surveys, Mortality","lastPublishedDoi":"10.21203/rs.3.rs-6878790/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6878790/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA large measles outbreak occurred in Yakusu Health Zone, Democratic Republic of the Congo, between Jan 2018 and June 2019. We describe the extent of the outbreak and it’s impact on the population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a retrospective household survey to describe the attack rate and various mortality measures, and to assess vaccination coverage both before and after a mass reactive vaccination campaign. We estimated the true outbreak size by extrapolating the attack rate and case fatality ratios to the population of Yakusu. We conducted geospatial analyses to describe the distribution of measles attack rate and vaccination coverage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e8,968 individuals were included in the survey, of whom 1,390 (15.5%, 95%CI 13.2-17.8) reported to have had measles during the recall period. The outbreak size was estimated as 22,068 (95% CI 18,980-25,553).\u003c/p\u003e\n\u003cp\u003eOverall case fatality ratio was 2.5% [95% CI 1.7-3.4]; measles-specific proportional mortality was 15.3% [95%CI 10.9-19.8]; and the all-cause mortality rate was 0.72 per 10,000 person-days [95% CI 0.61-0.82]. For children aged under 5 years, the overall attack rate was 45.7% [95% CI 39.6-51.9]; case fatality ratio was 4.9% [95% CI 3.4-6.3]; measles-specific proportional mortality was 35.2% [95%CI 26.0-44.5]; and all-cause mortality rate was 1.51 per 10,000 person-days [95% CI 1.19-1.84]. Children aged under 1 year had the greatest risk of death.\u003c/p\u003e\n\u003cp\u003eTwo-thirds of the target population had been vaccinated during routine Expanded Programme on Immunization (EPI, 67.9% [95%CI 62.2-73.6]) and during the campaign (67.7% [95%CI 61.6-73.8]). Coverage according to either EPI or campaign was 82.1% [95%CI 78.0-86.1]).\u003c/p\u003e\n\u003cp\u003eThere was a high degree of spatial overlap in vaccination coverage by EPI and campaign, with pockets of low coverage throughout Yakusu, within which the epidemic propagated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a high-impact epidemic, both in terms of attack rate and case fatality, with an elevated risk of dying for at least 90 days post-onset of disease. Reactive vaccination activities were effective at the individual level, but were implemented late, did not reach intended coverage, and were insufficiently targeted to ensure that previously unvaccinated children received vaccination, thereby leaving pockets of unvaccinated children among whom the outbreak appeared to persist.\u003c/p\u003e","manuscriptTitle":"Description of a large and deadly measles epidemic, Yakusu health zone, Democratic Republic of Congo, 2018-2019: A retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-16 07:52:59","doi":"10.21203/rs.3.rs-6878790/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0708cfcf-013e-4d5a-b2a9-863347a7bf91","owner":[],"postedDate":"June 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49936322,"name":"Epidemiology"}],"tags":[],"updatedAt":"2025-07-06T10:19:49+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-16 07:52:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6878790","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6878790","identity":"rs-6878790","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}