Summary
Background
DR Congo has the highest global burden of mpox, a disease caused by infection with the monkeypox virus. Over the last decades the incidence has risen, but recent analyses of epidemiological trends are lacking. We aimed to describe trends in suspected and confirmed mpox cases in DR Congo using epidemiological and laboratory mpox surveillance data collected from 2010 to 2023, and provide insights that can better inform the targeting and monitoring of control strategies.
Methods
We analysed aggregated national epidemiological surveillance data and individual-level laboratory data from 2010 to 2023. We calculated incidence based on suspected cases, case–fatality ratios, and percentage of laboratory-confirmed cases and assessed geospatial trends. Demographic, and seasonal trends were investigated using generalised additive mixed models.
Findings
Between Jan 1, 2010, and Dec 31, 2023, a total of 60 967 suspected cases and 1798 suspected deaths from mpox were reported in DR Congo (case-fatality ratio 2·9%). The number of reporting provinces increased from 18 of 26 provinces in 2010 to 24 of 26 provinces in 2023. The annual incidence increased from 2·97 per 100 000 in 2010 to 11·46 per 100 000 in 2023. The highest incidence (46·38 per 100 000) and case-fatality ratio (6·0%) were observed in children younger than 5 years. Incidence was higher in rural compared with urban areas. PCR testing was performed for 7438 suspected cases (12·2%), with 4248 (57·1%) of 7438 samples testing positive. Median age of confirmed cases (13·0 years [IQR 6·0–25·0]) remained stable, although the 95th percentile of age increased over time.
Interpretation
The incidence and geographical distribution of suspected mpox cases increased substantially since 2010. Improvements in surveillance and decentralised testing are essential to monitor mpox trends and direct interventions effectively, to address the public health emergency declarations issued in August 2024.
Funding
Belgian Directorate-General Development Cooperation and Humanitarian Aid; European and Developing Countries Clinical Trials Partnership; Research Foundation–Flanders; European Civil Protection and Humanitarian Aid Operations; Department of Economy, Science, and Innovation of the Flemish government; Canadian Institutes of Health Research; and the International Development Research Centre.
Introduction
Monkeypox virus is a zoonotic virus that originated in forested areas in Africa, but has undergone global expansion since 2022.1 The virus causes mpox, a disease characterised by fever, lymphadenopathy, and a typical papulo-pustular rash. The first human case was detected in DR Congo in 1970, and the country has been the epicentre of mpox ever since.1,2
Two distinct monkeypox virus clades are known to cause disease.3 Clade I is endemic in DR Congo and other central African countries and reported to be the most virulent, with case-fatality ratios ranging between1·4% and 10%.4,5 In 2024, genomic sequencing of strains from a large outbreak with human-to-human transmission in eastern DR Congo revealed significant phylogenetic divergence from other clade I strains, leading to the subdivision of clade I into Ia and Ib, with the new lineage named clade Ib.6 Clade II—divided into subclades IIa and IIb—was originally endemic in West Africa.1 However, in 2022 subclade IIb sparked a worldwide outbreak, causing over 90 000 confirmed cases in more than 100 countries.7 WHO declared a Public Health Emergency of International Concern from July 2022 to May 2023.
During the same period, clade I monkeypox virus infections also continued to increase, especially in DR Congo. Due to shifts in ecological factors and the cessation of smallpox vaccination (which provided cross-protection against mpox) the number of mpox cases began to rise steadily from 1980 onwards.8–10 Active surveillance for mpox was established after smallpox eradication, but these efforts were discontinued in 1986. In 2001, a national system of passive surveillance was initiated through the Integrated Disease Surveillance and Response (IDSR) system, a strategy developed by WHO to improve the collection, analysis, and use of health data for the timely detection, reporting, and response to priority diseases.11 Following the implementation of IDSR-based surveillance suspected mpox incidence rose rapidly, from 0·64 suspected cases per 100 000 population in 2001 to 2·84 cases in 2013,11 with spatial analysis by 2015 showing clusters located in rainforest communities.12
Since then, no new national-level analysis of mpox incidence has been done. Meanwhile, reports from DR Congo Ministry of Health (MoH) indicate a substantial increase in recent years, culminating in almost 15 000 reported suspected cases nationwide in 2023; the trend worsened in 2024, with over 15 000 cases reported from January to June.13,14 Additionally, clade I infections are increasingly detected in neighbouring countries, including Rwanda, Burundi, Uganda, and Kenya. Imported infections have also been reported outside Africa in Sweden, Thailand, India, Germany, and the UK.15,16 As a result, the Africa Centres for Disease Control and WHO issued new public health emergency declarations in August, 2024.17,18
The objective of this study was to describe trends in suspected and confirmed mpox cases in DR Congo using epidemiological and laboratory mpox surveillance data collected from 2010 to 2023. The findings aim to provide insights that can better inform the targeting and monitoring of control strategies.
Methods
Mpox surveillance in DR Congo
We conducted a retrospective analysis of national epidemiological surveillance and laboratory data in DR Congo. Mpox is one of 21 notifiable diseases in DR Congo. Four national institutes are involved in mpox surveillance: The Directorate of Epidemiological Surveillance (Direction de Surveillance Epidemiologique [DSE]) oversees surveillance of all notifiable diseases; the National Mpox Programme (Programme National de Lutte Contre le Monkeypox et les fièvres hémorragiques virales) conducts outbreak investigations; and the National Institute for Biomedical Research (Institut National de Recherche Biomédicale [INRB]) is the national reference laboratory. All activities are coordinated by the National Institute of Public Health (Institute National de la Santé Publique).
Surveillance is decentralised in a hierarchical system. The 26 provinces are divided into health zones (519 nationwide), which are further subdivided into 9621 health areas. The IDSR system conducts syndromic surveillance at the community level, where health-care workers report individuals who meet the clinical case definition as suspected cases to the health zone authorities. Cases are recorded in a weekly epidemiological survey and transmitted to the Provincial Health Division. After validation, the data is sent to the DSE, communicated to the relevant programmes, and stored electronically in the District Health Information Software (DHIS2). Reporting of suspected cases is often hampered by logistical challenges and underfunding.19
Mpox case definitions
Three possible definitions of a suspected case have been used during the study period
First, the MoH official case definition, in use since 2001, defines an mpox suspect case as a person presenting with a sudden onset of high fever followed by a vesicular-pustular rash predominantly on the face and present on the palms of the hands and soles of the feet; or presence of at least five smallpox-like scars.20,21 Second, the WHO Africa Regional Office-recommended case definition was incorporated into the national guidelines as an alternative, as of 2019.22 It states that a suspected case is a person with acute illness with fever over 38·3°C, intense headache, lymphadenopathy, back pain, myalgia, and intense asthenia, followed 1–3 days later by a progressively developing rash often beginning on the face (most dense) and then spreading elsewhere on the body, including soles of feet and palms of hand. Third, the Kinshasa School of Public Health and the United States Centers for Disease Control and Prevention apply a case definition as part of active surveillance efforts in Tshuapa Province, where a suspected case is any person with vesicular or pustular eruption with deep-seated and firm pustules and at least one of the following: fever preceding eruption, lymphadenopathy, or pustules or crusts on palms of hands and soles of feet (or both in combination).23 In all settings, a confirmed mpox case is defined as any suspected case who tests positive for monkeypox virus on real-time PCR.
Sample referral and laboratory investigations
In principle, each suspected case warrants investigation by the local surveillance team who collect data using a standardised case investigation form and biological samples (lesion swabs, crusts, or both; oropharyngeal swabs; blood samples; or a combination of any of the sample types, depending on availability of sampling devices at the local surveillance unit). Samples are shipped to the INRB laboratory in Kinshasa (or, as of November 2024, Goma), alongside the case investigation form. However, local health authorities often lack sufficient personnel and materials to investigate each case, leaving sample collection—if conducted—to first-line health-care workers, with the choice of sample type dependent on the available sampling materials.19
At the central laboratory, a PCR test targeting orthopoxviruses is performed (see Kinganda-Lusamaki and colleagues24 for details). Individuals who test positive on PCR for orthopoxviruses in any biological sample are considered to have mpox.24 Negative samples are PCR tested for varicella zoster virus (VZV), with no further testing for other diseases. Test results are entered into a Microsoft Excel database and shared with the DSE.
Data retrieval
We retrieved national surveillance data on suspected mpox cases, according to any of the three definitions, from 2010 to 2023 from the DHIS2 database of the DSE, aggregated per health zone and epidemiological week (appendix p 13). For 2023 only, the distribution of suspected cases across three age categories (age <5 years, age 5–15 years, and age >15 years) was available. Additionally, we obtained anonymised individual-level testing data from the INRB laboratory database for 2004–23. These data contain test results, alongside a limited set of variables derived from the case investigation forms accompanying the samples, including details on age, gender, health zone, illness onset date, and sample collection date. The DSE and laboratory databases are not linked. To calculate incidence, we retrieved health zone population estimates (from 2008–17) from DR Congo Essential Program on Immunization. Data on ethnicity was not available.
Data analyses
Using the national epidemiological surveillance data, we calculated suspected mpox case notifications and deaths, by year and by weekly moving average. The case–fatality ratio was calculated as number of reported suspected deaths divided by reported suspected cases for the same time period. Incidences per 100 000 were calculated as the number of suspected or confirmed cases divided by the estimated population of the health zone or province for a given week or year. Due to missing population data from 2018 onwards, and gaps in health zone data for certain years, we extrapolated the data by first calculating the mean yearly growth coefficient for each health zone. We then either back-calculated the estimated population size from the first known year or forward-calculated from the last known year.
We mapped the geographical distribution of suspected and confirmed cases and incidence by health zone and province, overall and by year. Shapefiles were obtained from the Humanitarian Data Exchange (https://data.humdata.org/).
To investigate differences in incidence between urban and rural areas, we used a generalised additive mixed model (GAMM),25 with a random intercept to account for year-to-year variation in incidence, and a cubic regression spline to model the possibly non-linear trend in incidence. We defined urban areas as health zones with population density over 300 inhabitants per square km (appendix p 5).26
We investigated seasonality of suspected mpox cases by modelling weekly suspected mpox incidence and monthly confirmed mpox count using a GAMM, with a yearly recurring seasonal effect and a long-term trend.27 We classified provinces according to three Köppen–Geiger climate zones (tropical rainforest, tropical savanna, and tropical monsoon climate).28 We allowed variations in first, the shape of the yearly recurring seasonal effect and the long-term trend functions by climate region, second, baseline incidence by climate region, and third, incidence levels over time. A correlation structure, selected based on the lowest Akaike information criterion (AIC), was used to capture temporal dependence between observations (appendix p 6).
From the individual-level laboratory data, we calculated the sampling ratio (number of suspected cases with at least one sample received in the lab divided by the number of notified suspected cases), testing ratio (number of suspected cases with at least one sample PCR tested divided by the number of notified suspected cases) and the positivity ratio (positive orthopoxviruses or monkeypox virus PCR result divided by the total number of tests). We mapped test numbers, testing ratios, and positivity ratios by province. Among mpox-confirmed individuals, we analysed gender and age distribution and performed quantile regression (5th, 50th, and 95th percentiles) to study trends in age over time.
The secondary use of aggregated surveillance and anonymised laboratory data was approved by DR Congo National Ethical Committee (472/CNES/MMS/2023) and the Institute of Tropical Medicine Antwerp Institutional Review Board (1699/23). As this study consists of retrospective analysis of routine surveillance data, obtaining individual informed consent was not required.
Role of the funding source
The funders had no role in the conceptualisation of the study, data acquisition or interpretation, writing of the manuscript, or publication of the findings.
Results
Between Jan 1, 2010, and Dec 31, 2023, a total of 60 967 suspected cases were reported in DR Congo (figure 1A), of which 4248 were laboratory-confirmed. Annual reported suspected cases varied from the 2302 cases in 2010, with a low of 2211 cases in 2011 to a high of 14 636 cases in 2023 (figure 1A). The annual incidence of reported suspected cases, was 2·97 per 100 000 people in 2010. Incidence increased to 6·49 per 100 000 inhabitants in 2020, decreased to 2·44 per 100 000 inhabitants in 2021, and rose again to 11·46 per 100 000 inhabitants in 2023 (figure 1B,C).
Figure 1. Evolutions in case notifications and deaths of mpox suspected cases in DR Congo, 2010–23.
(A) Suspected case notifications by year.
(B) Suspected cases per 100 000 population by year.
(C) Weekly observed incidence per 100 000 population of mpox suspected cases (red line) and moving average of the weekly incidence (grey line).
(D) Suspected yearly incidence of mpox cases stratified by age categories, in 2023†.
(E) Weekly observed case-fatality ratio (red line) with moving average over time (grey line); incidence estimates are shown above the bars.
(F) Case-fatality of suspected mpox cases stratified by age group in 2023.
*Case-fatality percentages are shown above each bar. †Years for which age distribution was available in cases and death notifications data.
The distribution according to age category (only available for 2023) showed that children younger than 5 years accounted for 35.6% of suspected cases (5207 of 14 638; incidence 46·38 per 100 000), children aged 5–15 years for 30·4% (4445 of 14 638; incidence 19·90 per 100 000), and individuals older than 15 years for 34·1% (4986 of 14 638; incidence 5·08 per 100 000; figure 1D, appendix pp 14–15). The aggregated database reports the total number of cases per health zone and the number of cases per age category per health zone. There was a small error in the database, in which the sum of the number of cases in the age categories differed from the reported total number of cases. The total number of cases for 2023 based on the age categories is 14 638; a difference of two compared with the total case count (14 636), small enough to not substantially change our analyses.
Between 2010 and 2023, a total of 1798 suspected mpox deaths were reported (case-fatality ratio 2·9% among the 60 967 suspected cases). The case-fatality ratio increased from 1.0% (22 deaths per 2302 cases) in 2010 to 4.6% (667 per 14 636 cases) in 2023 (figure 1E). Reported mortality in 2023 was 6.0% (313 deaths per 5207 cases) for children younger than 5 years, 4·2% (186 deaths per 4445 cases) for those aged 5–15 years, and 3·4% (168 deaths per 4986 cases) for individuals older than 15 years (figure 1F). Data on the exact cause of death were unavailable.
Among all 26 provinces, Sankuru reported the highest number of suspected infections: 15 923 cases and a mean annual incidence of 51·9 cases per 100 000 inhabitants (SD 31·5 cases per 100 000 inhabitants, figure 2A, B). Seven other provinces had a mean annual incidence greater than five cases per 100 000 population: Tshuapa (27·2 [SD 9·8]), Equateur (26·4 [SD 51·0]), Maï-Ndombe (17·8 [SD 18·9]), Bas-Uele (14·1 [SD 9·8]), Mongala (11·9 [SD 11·2]), Tshopo (7·7 [SD 8·2]) and Sud-Ubangi (6·2 [SD 2·7]). Four provinces (Nord-Ubangi, Maniema, Kasaï, and Kwango) had a mean annual incidence between one and five cases per 100 000. The other 14 provinces reported less than one case per 100 000 population annually (appendix pp 3–4).
Figure 2. Spatial distribution of mpox suspected case notifications and incidence by province in DR Congo, 2010–23.
Cumulative number of mpox suspected case notifications per province (A). Mean yearly incidence per province (B).
Suspected mpox cases expanded geographically in DR Congo over time. In 2010, suspected cases were reported in 18 of 26 provinces and 108 of 519 health zones. By 2023, suspected cases were reported from 24 of 26 provinces and 199 of 519 health zones (figure 3). Among the 12 provinces with a mean annual incidence higher than one per 100 000 population, eight provinces experienced at least a 50% increase in incidence between 2010 and 2023: Sankuru, Equateur, Maï-Ndombe, Bas-Uele, Tshopo, Sud-Ubangi, Kasaï, and Kwango (figure 4). Equateur had the most significant increase in incidence of suspected cases, from 17·2 in 2010 to 202.3 per 100 000 population in 2023, with 6820 cases reported in 2023 alone. Tshuapa, Mongala, and Nord-Ubangi had a small decrease in incidence (<50%). In Maniema province, the incidence peaked in 2010, declined to near zero levels in 2014, and then increased again in 2021 (appendix pp 3–4,16).
Figure 3. Spatial evolution in incidence of mpox suspect cases.
Yearly incidence of suspected mpox cases per province (A) and per health zone (B), from 2010 to 2023
Figure 4. Observed and smoothed yearly incidence of mpox suspected cases in provinces with an incidence of one or more per 100 000 population.
*Smoothed using a generalised additive model per province.
Incidence was 98·8% lower in urban than in rural areas (b –4·45 [SE 0·10]; p<0·001; figure 5A; appendix pp 4–5). A non-linear trend in weekly incidence of suspected mpox cases was observed in both urban (p<0·001) and rural (p=0·010) areas, with a substantial increase in rural zones and a more moderate rise in urban areas (appendix p 5).
Figure 5. Seasonal and ecological trends in weekly incidence of mpox suspected case notifications per 100 000 population over time.
(A) Predicted weekly incidence per 100 000 population of suspected mpox cases for rural and urban areas from 2010 to 2023 based on the GAMM.
(B) Predicted long-term trend (2010–23) in weekly incidence of mpox suspected cases based on the GAMM. Provinces were classified into three major Köppen–Geiger climate zones: tropical rainforest, tropical monsoon, and tropical savanna.
(C) Weekly mpox suspected case incidence (per 100 000 population) based on the observed data (grey), and model predictions based on the GAMM (red); by Köppen–Geiger climate zones*.
(D) Predicted long-term trend (from 2010 to 2023) in weekly incidence (per 100 000 population) of mpox suspected cases (top) and predicted yearly recurring seasonal effect (from 2010 to 2023) in weekly incidence (per 100 000 population) of mpox suspected cases (bottom), stratified by Köppen–Geiger climate zones*; based on the GAMM model.
GAMM = generalised additive mixed model. (s)time = smooth term for long-term non-linear trend in incidence expressed in weeks. s(week) = yearly recurring smoothed non-linear trend incidence expressed in weeks.
*As the province of Haut-Katanga is the only province in the subtropical climate zone and has mean annual incidence over all years of zero, it was further excluded from all seasonality analyses.
Incidence was highest in rainforest and monsoon climate zones compared with the savanna climate (figure 5B,C). The long-term trend was significantly non-linear for monsoon effective degrees of freedom ([edf] 8·412, p<0·001) and rainforest (8·333, p<0·001) climate zones, but not for savanna (2·344, p=0·061). We also found a yearly recurring pattern in all climate zones, with cases peaking from January to March and July to September in monsoon and rainforest climate zones (monsoon edf 6·341, p<0·001; rainforest 5·596, p<0·001; and savanna 2·267, p=0·009; figure 5C,D; appendix pp 6–12).
Between 2010 and 2023, samples from 7681 (12·6%) of 60 967 individuals were sent for laboratory confirmation (figure 6A). This sampling ratio varied from 4·7% in 2010 to 22·3% in 2017 (figure 6B), with an overall sampling ratio of 12·6% (7681 of 60 967). Testing was performed for 7438 samples of 7681 submitted, giving an overall testing ratio of 12·2% of suspected mpox cases (appendix p 17).
Figure 6. Trends in laboratory sample referral, laboratory testing, case confirmation, and age distribution of confirmed cases.
(A) Attrition plot with total number of mpox suspected cases 2010–23, number of cases with samples received at the central laboratory, number of suspected cases with samples received at the central laboratory, number of suspected cases with successfully performed laboratory analyses of samples, and number of suspected cases testing positive for OPXV on PCR.
(B) Yearly sampling ratio (proportion of mpox suspected cases for whom samples were received at the central laboratory) and yearly test positivity ratio (proportion of analysed samples that were positive on OPXV PCR) from 2010 to 2023.
(C) Yearly number of confirmed cases, from 2010 to 2023.
(D) Yearly incidence per 100 000 population of confirmed cases over time.
(E) Map of the cumulative number of cases for which mpox tests were requested at the central laboratory by province, from 2010 to 2023.
(F) Map of the overall test positivity ratio in percentages per province, from 2010 to 2023.
(G) Age distribution of confirmed mpox cases; 2010 to 2023.
(H) Quantile regression of age of confirmed mpox cases at 5th, 50th, and 95th percentile from 2004 to 2023*.
OPXV = orthopoxvirus. *For this analysis laboratory data were available from 2004 onwards. To use all available data and show long-term trends, all data were included.
Overall, 4248 (57·1%) of 7438 samples tested positive by orthopoxviruses PCR, 3158 (42·5%) tested negative, and 32 (0·4%) yielded uninterpretable results owing to amplification curve problems. Mpox was confirmed in 4248 (7·0%) of 60 967 suspected cases (figure 6A). The test positivity ratio was lowest (24 [22·2%] of 108) in 2010 and highest (229 [78·2%] of 293) in 2020 (figure 6B). The yearly number of confirmed mpox cases increased from 24 cases in 2010 to 393 in 2017, declined between 2018 and 2021, and surged to 1268 in 2023 (figure 6C, appendix p 2). The yearly incidence of confirmed cases followed a similar pattern, with incidence per 100 000 population increasing from 0·03 in 2010 to 0·99 in 2023 (figure 6D, appendix pp 2–4, 18–19). Among the 3158 individuals who tested negative for orthopoxviruses, 2758 (87·3%) were tested for VZV. Of these, 1174 (42·6%) tested positive.
The highest cumulative number of patient samples sent for testing came from Tshuapa (4171 samples), Equateur (671), Tshopo (514), Maï-Ndombe (315), Kwango (275), Sud-Ubangi (252), Maniema (143), Sankuru (119), Kwilu (119), and Kasaï (114). The remaining provinces sent under 100 samples each (figure 6E, appendix pp 3–4). Provinces with the highest overall test positivity ratio were Sankuru (83·3%), Tshopo (74·2%), Tshuapa (69·7%), Sud-Ubangi (57·0%), Mongala (54·1%), and Haut-Uele (50·9%). All other provinces had substantially lower (<50%) positivity ratios (figure 6F, appendix pp 3–4). The distribution of confirmed cases expanded geographically over time (appendix pp 20–21).
From 7681 individuals, a total of 8712 samples were received in the laboratory. These consisted of 4197 lesion swabs (48·2% of samples), 2325 blood samples (26·7% of samples), and 2190 crusts (25·1% of samples). Of the 4248 confirmed cases, 1911 (45·0%) were women, 2261 (53·2%) were men, and gender was not reported for 76 cases (1·8%; appendix p 22).
Following the exclusion of 183 individuals (4·3%) of the total 4248, for whom no age was available, the median age among mpox-confirmed cases was 13·0 years (IQR 6·0–25·0; figure 6G). The 5th and 50th percentile or median-over-time remained fairly stable (age increase 0·06 [95% CI 0·02–0·09]) and 0·19 years per year [95% CI 0·09–0·28], for the 5th and 50th percentile, respectively). However, over time the 95th percentile of age among cases increased by 0·57 per year (95% CI 0·29–0·86; figure 6H).
Discussion
Our analysis of national epidemiological and laboratory data over a 14-year period from 2010–23 shows a nearly four-fold increase in incidence of suspected mpox cases, from 2·97 per 100 000 in 2010 to 11·6 per 100 000 in 2023, with the greatest increase in 2023 versus 2022. This increase was accompanied by a substantial geographical expansion of the disease, especially in rural areas. The highest mortality among suspected cases was found in children younger than 5 years. Due to resource and logistical constraints, only a small fraction of suspected cases underwent confirmatory laboratory testing.
This report documents analyses of more than a decade of national epidemiological surveillance data and, to our knowledge, is the first to include the findings from laboratory-confirmed cases across the country over any time period. It provides insights into trends in suspected and confirmed mpox cases in DR Congo, the country with the greatest mpox burden, and highlights challenges for surveillance. Although the data are the best estimates of mpox incidence to date, there are limitations to this study. The IDSR surveillance framework is based on suspected rather than confirmed cases. Due to the limited sampling, only 12·2% of all suspected cases were tested, and around 60% of those tested positive. Incidence estimates based on suspected cases might, therefore, overestimate the true incidence. Conversely, passive surveillance probably underestimates the true incidence due to underreporting. Several barriers impede accurate disease reporting, such as low health care-seeking behaviour, insufficient training of health-care workers in remote areas, and inadequate communication and transport infrastructure.19 The accuracy of reporting is further hindered by the use of different case definitions for suspected mpox, and differences over time and by location in the fraction of cases tested. Since the reasons for sampling are not recorded, the direction of bias is unknown. Reliance on aggregated suspected case data and a lack of linkage between epidemiological and laboratory databases limits the possibility of detailed exploration of the data.
These limitations notwithstanding, these surveillance data show important trends, consistent with previous findings. Rimoin and colleagues documented a 20-fold increase in incidence in Sankuru province during 2006-07 compared compared with 1981–86.8 Analysis of surveillance data from 2001–2013 also indicated an increase in annual incidence in DR Congo from 0·64 to 2·84 per 100 000 inhabitants.11
The rising incidence of reported mpox could reflect an actual increase in cases, variations in disease awareness and reporting, or a combination of both. From 2010 to 2021, incidence rose slowly but steadily, followed by a sharp decline in 2021, likely due to disruptions in surveillance caused by the COVID-19 pandemic rather than a genuine decline in cases.29 The subsequent increase in incidence in 2022 and 2023 coincided with the global outbreak of monkeypox virus clade IIb, although there was no documented epidemiological relationship. This increase might therefore partly be due to increased attention to the disease. However, the geographical expansion indicates rising incidence resulting from increased transmission.6,30
The precise factors driving this expansion are yet to be fully understood. Potential factors include the expansion and migration of the animal reservoir, particularly in rural areas, linked to forest exploitation, loss of biodiversity, and the resulting increase in rodent populations.9,10,31 Of almost 15 000 suspected cases notified in 2023, over 6000 were from densely forested areas in Equateur province, where a large outbreak is ongoing.14 In addition, clade I transmission patterns are shifting, with a growing trend towards sustained human-to-human transmission, including through sexual contact.6,14 This is most evident in the clade Ib outbreak that emerged in eastern DR Congo in South Kivu since September 2023, and has spread within DR Congo, including to internally displaced people in North Kivu,32 and to several neighbouring countries.6 Population mobility, including displacement due to armed conflict, has been suggested as a contributing factor.32
Most suspected mpox infections were recorded among children younger than 15 years. Potential reasons for this include the large size of the population who are younger than 15 years; differences in exposure to the animal reservoir; or the gradual buildup of immunity with age in highly endemic areas. Additionally, since these numbers are based on suspected cases, some misclassification with other childhood illnesses is likely. The incidence is also likely influenced by declining population immunity following the eradication of smallpox.33,34 The median age of laboratory-confirmed cases did not substantially increase between 2004 and 2024. However, the 95th percentile of ages of confirmed cases increased steadily with time, indicating that the upper age limits shift as the cohort of unvaccinated individuals gets older.
Among all reported suspected cases, we observed a case–fatality ratio of 2·9%. This figure should be interpreted cautiously, as it is based on deaths among suspected cases, with no data about cause of death; and no data about deaths among confirmed cases. The case–fatality ratio might be overestimated due to the overrepresentation of severe cases or underestimated due to the loss of follow-up in reported cases. Early epidemiological studies reported a crude case–fatality ratio of approximately 10%.35 However, a more recent prospective clinical characterisation study, in Sankuru Province, reported a case–fatality ratio of only 1·4%.5
Few studies have explored mpox seasonality in DR Congo, with mixed results. An active surveillance study, conducted in Sankuru Province,8 found no significant seasonal trends. However, consistent with earlier research from 198536 and more recent studies12,37 we observed a recurring pattern over time in monsoon and rainforest climate zones, with suspected cases peaking from January to March and July to September. Nevertheless, further detailed studies are needed to determine whether these patterns are influenced by climatic factors or result from variations in surveillance practices.
With the rising incidence of clade I mpox in DR Congo and beyond, robust national surveillance data are vital for guiding and monitoring response efforts, including vaccination campaigns. This study highlights crucial areas in mpox surveillance that need strengthening, such as comprehensive demographic data reporting, harmonising case definitions, and expanding decentralised testing. These improvements are crucial for obtaining accurate estimates of incidence and mortality, which are necessary for evaluating the effectiveness of interventions in response to the public health emergency declarations made in August 2024.
Supplementary Material
Research in context.
Evidence before this study
DR Congo has the highest burden of mpox globally, with endemic transmission caused by Clade I monkeypox virus. After the cessation of smallpox vaccination in 1980, mpox incidence in DR Congo began to rise, but detailed analyses of epidemiological data have been sporadic. We searched PubMed from database inception to June 2024, for reports in English or French describing mpox epidemiology in DR Congo, using the search term (“mpox” or “monkeypox”) and (“surveillance”) and (“Congo”) and (“incidence”). Of 15 reports published between 2010 and 2024, three were relevant. A comparison of mpox incidence in 1986 versus 2006 in one highly endemic health zone in DR Congo found a significant increase from 7.2 to 144.2 per 100 000 population. Data based on the WHO Integrated Disease Surveillance and Response framework from 2001 to 2013 showed a rise in the estimated national incidence, from 0.64 to 2.84 per 100 000 population. Analysis of the spatio-temporal dynamics of mpox at health zone level from 2000 to 2015 found that suspected mpox cases were concentrated in dense rainforest regions in Sankuru and Tshuapa provinces, with temporal expansion to neighbouring districts during the investigational period. No updated analyses have been published since 2015.
Added value of this study
This study provides a comprehensive analysis of suspected and confirmed mpox cases in DR Congo, using 14 years of national epidemiological data from 2010 to 2023. The data includes weekly aggregated reports of suspected mpox cases by health zone from the national surveillance program, as well as individual-level laboratory testing data from the national mpox referral laboratory. Our findings provide an in-depth account of the persistent rise in incidence of suspected mpox cases and the expanding geographic distribution across the country. The report provides details on geographical hotspots of suspected mpox cases and different age groups at risk, including mortality and morbidity by age. Moreover, the report highlights key gaps in the surveillance system and the low degree of confirmatory testing. Lastly, the study describes a shift in age pattern among mpox-confirmed cases, likely related to waning population immunity after the cessation of routine smallpox vaccination following variola virus eradication in 1980.
Implications of all the available evidence
The available evidence indicates that the incidence of suspected mpox cases has increased over time and geographical space in DR Congo, with an accelerated rate in recent years. Since the start of 2024, over 30 000 suspected mpox cases have been notified. Concurrent outbreaks have been reported at multiple locations in the country, and extended human-to-human transmission events have been reported to occur. This study provides vital insights into the trends of suspected and confirmed monkeypox virus infections in DR Congo which has been the epicentre of mpox since the first human cases were identified in 1970. It highlights significant gaps in mpox surveillance and equips public health actors with the context needed to understand the rising number of mpox cases. These insights will be instrumental in directing response efforts, including enhancing epidemiological surveillance, improving case management, expanding decentralised diagnostics, and implementing targeted vaccination campaigns in response to the mpox public health emergency declarations by the Africa Centers for Disease Control and Prevention and WHO in August 2024.
Acknowledgements
During the preparation of this work the authors made use of ChatGPT version 3.5 for assistance in the phrasing of parts of text. After using this tool, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication. We are grateful to all staff involved in one or more levels of mpox surveillance, especially those offering surveillance at the primary health care level, involved in communicating case notifications and sampling of suspected cases. This work was funded by the Belgian Directorate-General Development Cooperation and Humanitarian Aid, the Research Foundation – Flanders (FWO, grant number G096222N to EBo, LL and 12B1M24N to CVD), the European Civil Protection and Humanitarian Aid Operations (ECHO), the African Coalition for Epidemic Research Response (ALERRT) EDCTP2 grant number RIA2016E-1612, the Global Health EDCTP3 grant agreement (grant number 101195465). EBa, EDV, and IB are members of the Institute of Tropical Medicine’s Outbreak Research Team, financially supported by the Department of Economy, Science, and Innovation of the Flemish government (EWI). Additional support was provided by the International Mpox Research Consortium (IMReC) through funding from the Canadian Institutes of Health Research and International Development Research Centre (Grant No. 202209MRR-489062-MPX-CDAA-168421).
Footnotes
Contributors EBa, RD, LL, and PMK conceptualised the study, wrote the protocol and secured relevant ethical approvals. EBa, RD, EDV, EHV, SSN, AM, FM, AAA, EM, TK, CK, EK-L, TW-B, AA-A, JCM-C, DM-B, J-JM-T, RS, SA-M, and PM-K contributed to data curation and compilation. EBa, RD, EDV, LL, EHV, AM, FM, EM, TK, and PM-K had full access to the data. EBa, RD, EDV, CK, NH, and LL contributed to data analysis. EBa, RD, EDV, and LL wrote the first draft of the manuscript. SA-M, LL, and PMK contributed to supervision. All authors contributed to review and approved the final version of the manuscript. This activity was reviewed by the US Centers for Disease Control and Prevention (CDC), deemed not research, and was conducted consistent with federal law and CDC policy. The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the CDC.
Declaration of interests LL has received institutional consultancy fees from BioNtech and institutional research funding from Sanofi; both not relevant for this work. JK has provided expert witness reports for the Treasury Board of Canada not relevant to this work. JK has also received mpox research funding from the Canadian Institutes of Health Research and the International Development Research Centre in open funding competitions. All other authors declare no conflict of interest.
Contributor Information
Eugene Bangwen, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.
Ruth Diavita, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.
Elise De Vos, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Emmanuel Hasivirwe Vakaniaki, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo.
Sabin Sabiti Nundu, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo.
Annie Mutombo, Department of Epidemiological Surveillance, Ministry of Health, Kinshasa, Democratic Republic of the Congo.
Felix Mulangu, Department of Epidemiological Surveillance, Ministry of Health, Kinshasa, Democratic Republic of the Congo.
Aaron Aruna Abedi, Department of Epidemiological Surveillance, Ministry of Health, Kinshasa, Democratic Republic of the Congo.
Emile Malembi, Hemorrhagic Fever and Monkeypox Program, Ministry of Health, Kinshasa, Democratic Republic of the Congo.
Thierry Kalonji, Hemorrhagic Fever and Monkeypox Program, Ministry of Health, Kinshasa, Democratic Republic of the Congo.
Cris Kacita, National Institute of Public Health, Ministry of Health, Kinshasa, Democratic Republic of the Congo.
Eddy Kinganda-Lusamaki, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; TransVIHMI (Recherches translationnelles sur le VIH et les maladies infectieuses endémiques et émergentes), Université de Montpellier, French National Research Institute for Sustainable Development, INSERM, Montpellier, France.
Tony Wawina-Bokalanga, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Ministry of Health, Kinshasa, Democratic Republic of the Congo; Department of Medical Biology, University Hospital of Kinshasa, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
Cécile Kremer, Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium.
Isabel Brosius, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Christophe Van Dijck, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Prof Emmanuel Bottieau, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Koen Vercauteren, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Adrienne Amuri-Aziza, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo.
Jean-Claude Makangara-Cigolo, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Ministry of Health, Kinshasa, Democratic Republic of the Congo; Department of Medical Biology, University Hospital of Kinshasa, University of Kinshasa, Kinshasa, Democratic Republic of the Congo; Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland.
Elisabeth Muyamuna, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo.
Elisabeth Pukuta, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo.
Beatrice Nguete, Kinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
Didine Kaba, Kinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
Joelle Kabamba, US Centers for Disease Control and Prevention, Atlanta, GA, USA.
Christine M Hughes, US Centers for Disease Control and Prevention, Atlanta, GA, USA.
Olivier Tshiani-Mbaya, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Ministry of Health, Kinshasa, Democratic Republic of the Congo; Department of Medical Biology, University Hospital of Kinshasa, University of Kinshasa, Kinshasa, Democratic Republic of the Congo; Frederick National Laboratory, Leidos Biomedical Research, Clinical Monitoring Research Program Directorate, Frederick, MD, USA.
Prof Anne W Rimoin, Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA, USA.
Nicole A Hoff, Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA, USA.
Jason Kindrachuk, Department of Medical Microbiology & Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada.
Prof Niel Hens, Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.
Martine Peeters, TransVIHMI (Recherches translationnelles sur le VIH et les maladies infectieuses endémiques et émergentes), Université de Montpellier, French National Research Institute for Sustainable Development, INSERM, Montpellier, France.
Prof Nicola Low, Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Andrea M McCollum, US Centers for Disease Control and Prevention, Atlanta, GA, USA.
Robert Shongo, Hemorrhagic Fever and Monkeypox Program, Ministry of Health, Kinshasa, Democratic Republic of the Congo.
Daniel Mukadi-Bamuleka, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Ministry of Health, Kinshasa, Democratic Republic of the Congo; Department of Medical Biology, University Hospital of Kinshasa, University of Kinshasa, Kinshasa, Democratic Republic of the Congo; Rodolphe Merieux INRB-Goma Laboratory, Goma, Democratic Republic of the Congo.
Prof Jean-Jacques Muyembe-Tamfum, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo.
Prof Steve Ahuka-Mundeke, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Ministry of Health, Kinshasa, Democratic Republic of the Congo; Department of Medical Biology, University Hospital of Kinshasa, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
Laurens Liesenborghs, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.
Placide Mbala-Kingebeni, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Ministry of Health, Kinshasa, Democratic Republic of the Congo; Department of Medical Biology, University Hospital of Kinshasa, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
Data availability statement
De-identified data used in this study will be made available upon reasonable request via itmresearchdataaccess@itg.be. For more information about the programme see Mpox Biology, Outcome, Transmission and Epidemiology project.
References
- 1.Van Dijck C, Hoff NA, Mbala-Kingebeni P, et al. Emergence of mpox in the post-smallpox era—a narrative review on mpox epidemiology. Clin Microbiol Infect. 2023;29:1487–92. doi: 10.1016/j.cmi.2023.08.008. [DOI] [PubMed] [Google Scholar]
- 2.Ladnyj D, Ziegler P, Kima E., 3 A human infection caused by monkeypox virus in Basankusu Territory, Democratic Republic of the Congo. Bull World Health Organ. 1972;46:593–97. [PMC free article] [PubMed] [Google Scholar]
- 3.Likos AM, Sammons SA, Olson VA, et al. A tale of two clades: monkeypox viruses. J Gen Virol. 2005;86:2661–72. doi: 10.1099/vir.0.81215-0. [DOI] [PubMed] [Google Scholar]
- 4.Rimoin AW, Kisalu N, Kebela-Ilunga B, et al. Endemic human monkeypox, Democratic Republic of Congo, 2001–2004. Emerg Infect Dis. 2007;13:934–37. doi: 10.3201/eid1306.061540. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Pittman PR, Martin JW, Kingebeni PM, et al. Clinical characterization and placental pathology of mpox infection in hospitalized patients in the Democratic Republic of the Congo. PLoS Negl Trop Dis. 2023;17:e0010384. doi: 10.1371/journal.pntd.0010384. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Vakaniaki EH, Kacita C, Kinganda-Lusamaki E, et al. Sustained human outbreak of a new MPXV clade I lineage in eastern Democratic Republic of the Congo. Nat Med. 2024;30:2791–95. doi: 10.1038/s41591-024-03130-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Mitjà O, Ogoina D, Titanji BK, et al. Monkeypox. Lancet. 2023;401:60–74. doi: 10.1016/S0140-6736(22)02075-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Rimoin AW, Mulembakani PM, Johnston SC, et al. Major increase in human monkeypox incidence 30 years after smallpox vaccination campaigns cease in the Democratic Republic of Congo. Proc Natl Acad Sci USA. 2010;107:16262–67. doi: 10.1073/pnas.1005769107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Islam MM, Dutta P, Rashid R, et al. Pathogenicity and virulence of monkeypox at the human-animal-ecology interface. Virulence. 2023;14:2186357. doi: 10.1080/21505594.2023.2186357. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Mandja BA, Handschumacher P, Bompangue D, et al. Environmental drivers of monkeypox transmission in the Democratic Republic of the Congo. EcoHealth. 2022;19:354–64. doi: 10.1007/s10393-022-01610-x. [DOI] [PubMed] [Google Scholar]
- 11.Hoff NA, Doshi RH, Colwell B, et al. Evolution of a disease surveillance system: an increase in reporting of human monkeypox disease in the Democratic Republic of the Congo, 2001-2013. Int J Trop Dis Health. 2017;25:1–10. doi: 10.9734/IJTDH/2017/35885. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Mandja BM, Brembilla A, Handschumacher P, et al. Temporal and spatial dynamics of monkeypox in Democratic Republic of Congo, 2000-2015. EcoHealth. 2019;16:476–87. doi: 10.1007/s10393-019-01435-1. [DOI] [PubMed] [Google Scholar]
- 13.Ministry of Health DR Congo. [accessed Oct 1, 2024];Daily report of the mpox epidemic in DR Congo—SITREP Number 52 Kinshasa. 2024 Sept 21; https://reliefweb.int/report/democratic-republic-congo/rapport-journalier-de-lepidemie-de-mpox-en-rdc-sitrep-ndeg52-donnees-du-19-septembre-2024-semaine-epidemiologique-38 .
- 14.World Health Organization. Disease outbreak news; mpox (monkeypox) in the Democratic Republic of the Congo. 2024. Jun 14, [accessed Sept 28, 2024]. https://www.who.int/emergencies/disease-outbreak-news/item/2024-DON522 .
- 15.World Health Organization. [accessed Oct 5, 2024];Mpox: multi-country external situation report #37. 2024 Sept 22; https://www.who.int/publications/m/item/multi-country-outbreak-of-mpox--external-situation-report--37---22-september-2024 .
- 16.Kmietowicz Z. UK confirms first case of clade Ib mpox. BMJ. 2024;387:q2406. doi: 10.1136/bmj.q2406. [DOI] [PubMed] [Google Scholar]
- 17.World Health Organization. WHO Director-General declares mpox outbreak a public health emergency of international concern. 2024. Aug 14, [accessed Sept 28, 2024]. https://www.who.int/news/item/14-08-2024-who-director-general-declares-mpox-outbreak-a-public-health-emergency-of-international-concern . [PMC free article] [PubMed]
- 18.Ndembi N, Folayan MO, Ngongo N, et al. Mpox outbreaks in Africa constitute a public health emergency of continental security. Lancet Glob Health. 2024;12:e1577–79. doi: 10.1016/S2214-109X(24)00363-2. [DOI] [PubMed] [Google Scholar]
- 19.Mande G, Akonda I, De Weggheleire A, et al. Enhanced surveillance of monkeypox in Bas-Uélé, Democratic Republic of Congo: the limitations of symptom-based case definitions. Int J Infect Dis. 2022;122:647–55. doi: 10.1016/j.ijid.2022.06.060. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Ministere de la Santé de la RDC. Programme national de lutte contre le monkeypox et les fievres hemorragiques virales. Guide de prise en charge des épidémies dans la zone de santé: monkeypox. 2nd edn. 2012. Jul, [Google Scholar]
- 21.Ministere de la Santé de la RDC. Programme national de lutte contre le monkeypox et les fievres hemorragiques virales. 4th edn. Manuel de formation sur le Monkeypox; 2023. Variole du Singe. [Google Scholar]
- 22.World Health Organization. Technical guidelines for integrated disease surveillance and response in the WHO African region Booklet two: sections 1, 2 and 3. 3rd edn. 2019. [accessed Sept 29, 2024]. https://www.afro.who.int/publications/technical-guidelines-integrated-disease-surveillance-and-response-african-region-third . [Google Scholar]
- 23.Whitehouse ER, Bonwitt J, Hughes CM, et al. Clinical and epidemiological findings from enhanced monkeypox surveillance in Tshuapa Province, Democratic Republic of the Congo during 2011-2015. J Infect Dis. 2021;223:1870–78. doi: 10.1093/infdis/jiab133. [DOI] [PubMed] [Google Scholar]
- 24.Kinganda-Lusamaki E, Baketana LK, Ndomba-Mukanya E, et al. Use of mpox multiplex serology in the identification of cases and outbreak investigations in the Democratic Republic of the Congo (DRC) Pathogens. 2023;12:916. doi: 10.3390/pathogens12070916. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wood SN. Generalized additive models: an introduction with R. 2nd edn. Chapman and Hall/CRC; 2017. [Google Scholar]
- 26.European Commission. Applying the degree of urbanisation – a methodological manual to define cities, towns and rural areas for international comparisons – 2021 edition. Publications Office of the European Union; 2021. [accessed July 29. 2024]. https://ec.europa.eu/eurostat/web/products-manuals-and-guidelines/-/ks-02-20-499 . [Google Scholar]
- 27.Cabrera M, Taylor G. Modelling spatio-temporal data of dengue fever using generalized additive mixed models. Spat Spatio-Temporal Epidemiol. 2019;28:1–13. doi: 10.1016/j.sste.2018.11.006. [DOI] [PubMed] [Google Scholar]
- 28.Dinerstein E, Olson D, Joshi A, et al. An ecoregion-based approach to protecting half the terrestrial realm. Bioscience. 2017;67:534–45. doi: 10.1093/biosci/bix014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Tannor EK, Amuasi J, Busse R, et al. The impact of COVID-19 on health service utilization in sub-Saharan Africa—a scoping review. BMC Glob Public Health. 2024;2:51. doi: 10.1186/s44263-024-00083-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Charniga K, McCollum AM, Hughes CM, et al. Updating reproduction number estimates for mpox in the Democratic Republic of Congo using surveillance data. Am J Trop Med Hyg. 2024;110:561–68. doi: 10.4269/ajtmh.23-0215. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Simpson K, Heymann D, Brown CS, et al. Human monkeypox – after 40 years, an unintended consequence of smallpox eradication. Vaccine. 2020;38:5077–81. doi: 10.1016/j.vaccine.2020.04.062. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Mukadi-Bamuleka D, Kinganda-Lusamaki E, Mulopo-Mukanya N, et al. First imported cases of MPXV clade Ib in Goma, Democratic Republic of the Congo: implications for global surveillance and transmission dynamics. medRxiv. 2024 doi: 10.1101/2024.09.12.24313188v1. published online Sept 16 (preprint) [DOI] [Google Scholar]
- 33.Taube JC, Rest EC, Lloyd-Smith JO, Bansal S. The global landscape of smallpox vaccination history and implications for current and future orthopoxvirus susceptibility: a modelling study. Lancet Infect Dis. 2023;23:454–62. doi: 10.1016/S1473-3099(22)00664-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Bunge EM, Hoet B, Chen L, et al. The changing epidemiology of human monkeypox–a potential threat? A systematic review. PLoS Negl Trop Dis. 2022;16:e0010141. doi: 10.1371/journal.pntd.0010141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Jezek Z, Grab B, Szczeniowski M, Paluku KM, Mutombo M. Clinico-epidemiological features of monkeypox patients with an animal or human source of infection. Bull World Health Organ. 1988;66:459–64. [PMC free article] [PubMed] [Google Scholar]
- 36.Arita I, Jezek Z, Khodakevich L, Ruti K. Human monkeypox: a newly emerged orthopoxvirus zoonosis in the tropical rain forests of Africa. Am J Trop Med Hyg. 1985;34:781–89. doi: 10.4269/ajtmh.1985.34.781. [DOI] [PubMed] [Google Scholar]
- 37.Besombes C, Mbrenga F, Gonofio E, et al. Seasonal patterns of mpox index cases, Africa, 1970-2021. Emerg Infect Dis. 2024;30:1017–21. doi: 10.3201/eid3005.230293. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
De-identified data used in this study will be made available upon reasonable request via itmresearchdataaccess@itg.be. For more information about the programme see Mpox Biology, Outcome, Transmission and Epidemiology project.