Monkeypox outbreaks in the context of the COVID-19 pandemic: Network and clustering analyses of global risks and modified SEIR prediction of epidemic trends

Monkeypox (MPX) is a zoonotic infection caused by the monkeypox virus (MPXV). Direct contact with infected human or animal secretions or contaminated objects is the primary transmission route. Historically, human MPX infections were primarily reported in West and Central Africa, with non-African cases typically linked to travel to endemic regions. In 2022, however, MPX experienced dramatic global spread with sustained human-to-human transmission, leading to a multicountry outbreak in non-endemic countries and a global health emergency. By 16 August 2022, approximately 37,000 cases had been reported across six continents, many in countries reporting MPX for the first time. Concurrently, the ongoing COVID-19 pandemic poses added pressure on health systems, raising concerns about overlapping risks. The study aims to assess emerging spatiotemporal risk factors for MPX infection in the context of COVID-19 and to predict global epidemiological trends to inform response strategies. The authors note shifting transmission patterns, including the role of human mobility, demographic changes in susceptible populations (notably MSM), waning smallpox-derived immunity (especially under age 40), and potential environmental and socioeconomic determinants, motivating a comprehensive, multidimensional risk assessment and predictive modeling approach.

The paper situates the 2022 MPX outbreak in contrast to historical patterns, drawing on literature that identifies prior risk factors such as HIV prevalence, population density, demographic characteristics, environmental variables (forest cover, temperature, precipitation), biodiversity, and socioeconomic conditions. Historically, children under 15 were considered at higher risk with no major gender differences, whereas recent outbreaks disproportionately involve adult males, many identifying as MSM. Literature also highlights the shared orthopoxvirus lineage of MPXV and smallpox, implying cross-immunity and increased risk among those under 40 due to cessation of smallpox vaccination around 1980. Prior work has suggested roles for human mobility and international travel, though these relationships were not comprehensively established at a global scale before this study. The authors synthesize these strands to motivate examining multiple dimensions, including mobility, health system capacity, and COVID-19 dynamics, in explaining contemporary MPX spread.

Study design and overview: The authors conducted a longitudinal, global, country-level analysis to (1) compare historical (2001–2021) and current (2022) MPX risk factors, (2) identify key factors associated with the 2022 outbreak, (3) cluster countries by risk profiles, and (4) predict epidemic trends across continents via a modified SEIR model. Analyses followed GATHER guidelines and were implemented in R 4.1.1 and Python 3.8; maps were generated in ArcGIS 10.7. Data sources: MPX case data (1970–2022, with most cases reported since 2001) were compiled from GIDEON, the Global Health team repository, and the literature. MPX prevalence was summarized for two periods: 2001–2021 and 31 Jan–16 Aug 2022. Countries were categorized as endemic or imported based on WHO reports. Additional data included 21 explanatory variables across seven dimensions: socioeconomics (population density; population aged under 40; education level; GDP per capita; GDP growth; legal same-sex marriage; MSM population size), MPXV-associated biodiversity, environment (forest area, precipitation, temperature), health burden (HIV infection; COVID-19 infection), behavior (overweight; low physical activity), health services (HAQ index; IHR index; health expenditure), and mobility (inbound travelers; air passengers; international flight arrivals). For 2022 analyses, explanatory variables used the most recent values; COVID-19 cases covered 1 Jan–16 Aug 2022; flight arrivals were from April–May 2022. For 2001–2021 analyses, country-level explanatory variables were averaged over the period. Gray model: A univariate first-order gray model GM(1,1) was fit using annual global MPX cases from 2001–2021 to forecast 2022–2024 case counts (details in supplementary files). Correlation-based network analysis: Spearman’s rank correlations identified associations between MPX cases and the 21 variables (significance threshold p<0.05; reported associations with |r|≥0.3). Significant pairs formed networks where edge widths represented −log10(p-value). Using the leading eigenvector community detection in igraph, variables were grouped; those highly associated with MPX formed the MPX risk group (main risk factors). Multivariate regression: Negative binomial regression assessed associations between MPX cases and main risk factors, selecting the best model by AIC. Non-significant covariates (p>0.05) were removed. Interaction between international flight arrivals and COVID-19 infections was evaluated. Clustering analysis: Key comprehensive risk factors informed k-means clustering of countries (k=1–9 examined; optimal k selected via the gap statistic). Countries with missing data were excluded. Clusters were mapped and characterized by risk levels and attributes. Modified SEIR (Flight-SEIR) model: A continent-level SEIR model was modified to incorporate (a) international flight arrivals, (b) age-structured susceptibility reflecting waning smallpox-derived immunity (susceptible population = under-40 + (1/5.2)×over-40), and (c) a breakpoint on 23 June 2022 to represent increased global attention and interventions, fitting separate transmission rates before (βi1) and after (βi2) 23 June. Equations included movement of S and E across continents based on passenger flows; I and R cross-continental flows were set to zero (assumptions: symptomatic infected do not travel; recovered travel negligible early on). Incubation rate σ=1/13 (latent period), recovery rate γ=1/21 (recovery period). Parameters βi1 and βi2 were fit by minimizing mean squared error between predicted and observed cumulative confirmed cases for each continent. Model fit was evaluated by NMSE (lower is better). Statistical analysis: Continuous variables were summarized by medians (IQR) and compared by Kruskal–Wallis or Wilcoxon tests; categorical variables by counts/percentages and chi-square tests.

- Case burden and distribution: Since 2001, 83,622 MPX cases were recorded worldwide: 46,698 historical cases (2001–2021) across 16 countries and 36,924 cases in the current epidemic across 88 countries as of 16 Aug 2022. In the current outbreak, 90.9% of infected countries were imported countries; 86.4% reported their first MPX infections. Europe reported 19,043 cases in 37 countries (97.3% new-onset countries) and Northern America 12,904 cases in five countries (75.0% new-onset). - Shift in risk factors: Historically (2001–2021), MPX infections correlated mainly with HIV prevalence and population density. In 2022, multiple factors were associated with MPX in imported countries across socioeconomics (GDP, legal same-sex marriage, MSM population size, age), health burden (HIV and COVID-19 infections), health services (IHR, HAQ, health expenditure), and mobility (international flight arrivals, air passengers, inbound travelers). Network analysis highlighted seven main factors: international flight arrivals, COVID-19 infection, MSM population size, air passengers, HIV infection, IHR, and inbound travelers. - Multivariate regression (negative binomial): After adjusting for the interaction between international flight arrivals and COVID-19 infections, both remained significant predictors of MPX case counts: per one million flight arrivals, IRR=1.514 (95% CI: 1.402–1.636; p<0.001); per one million COVID-19 cases, IRR=1.286 (95% CI: 1.223–1.353; p<0.001); interaction term IRR=0.985 (95% CI: 0.982–0.988; p<0.001). MSM population size, HIV infection, and IHR were not significant in the final adjusted model (p>0.05). - Flight-SEIR model performance and R0: The modified model fit reported data well (continent-level NMSE 0.004–0.030). Early stage (pre-23 June 2022) showed high transmission across continents, with R0 approximately: Europe/Oceania/Northern America/Latin America, 7.01–7.84; Asia, 3.68; Africa, 1.61. Current stage (post-23 June) transmission declined substantially except in Africa; median R0 for medium-high-risk clusters fell from 7.01 to 1.35, while low-risk clusters remained ~1.61–1.37. By continent in the current stage: Latin America R0≈4.13; Northern America R0≈3.51; Oceania R0≈1.67; Europe R0≈1.35; Asia R0≈0.70. - Epidemic trajectory: Although Europe had the highest cumulative cases as of mid-August 2022, projections indicated Northern America and Latin America would overtake Europe by autumn 2022 if trends persisted. - Country risk clusters (k-means): Of 141 countries/regions, 56 were excluded for missing data; remaining countries formed three clusters: High-risk cluster (n=24; 31,639 cases; all members reporting cases) concentrated in Western Europe and Northern America, with high mobility, higher socioeconomic indicators, high COVID-19 burden, larger MSM populations, and higher early-stage R0 (median 7.017). Low-risk cluster (n=47; 36 cases; 12.8% of members with cases) mainly in Africa and South Asia, with opposite characteristics and lower early-stage R0 (median 1.605). Medium-risk cluster (n=70; 4,723 cases; 55.7% of members with cases) largely in Latin America and Asia, intermediate in characteristics. - Gray-model forecasting: The GM(1,1) forecast for 2022 (4,715 cases; C value=0.26; p=0.80) was far exceeded by observed 2022 cases by 16 Aug, underscoring dramatic, unanticipated growth.

The findings address the research questions by demonstrating that risk determinants for MPX have shifted from historical patterns to a multifactorial profile in 2022, with human mobility emerging as a key driver in the global spread, particularly as COVID-19-related travel restrictions eased. The significant associations of international flight arrivals and COVID-19 burden with MPX cases, including their interaction, suggest that COVID-19 influences MPX dissemination both via policy-mediated mobility changes and possibly through behavioral and immunological pathways. The Flight-SEIR model, incorporating mobility, age-structured susceptibility, and a post–June 23 transmission shift, captured observed trends well and quantified declines in transmission in response to heightened awareness/interventions, with persistent higher R0 in Northern and Latin America. The country-level clustering provides a practical stratification for risk management, indicating where surveillance, community engagement, and resources might be prioritized. The results have broad relevance for infectious disease preparedness, highlighting that expanding travel networks amplify vulnerability and that health systems in regions with high COVID-19 and MPX burdens face dual pressures. Additionally, the observed association with MSM population size underscores the importance of targeted, non-stigmatizing health education, community engagement, and STI screening in affected communities. Lessons from COVID-19—rapid communication, risk-aware behavior, and timely interventions—should inform MPX control strategies.

The study identifies temporal and spatial variation in MPX infection drivers and underscores the value of multidimensional risk assessment. Compared to historical drivers (HIV prevalence, population density), contemporary MPX risk is shaped by human mobility, COVID-19 burden, MSM population size, and socioeconomic and health system factors. The modified Flight-SEIR model predicts that Northern America and Latin America will face greater MPX risks than Europe in the near term, with ongoing transmission in most regions. Policymakers should strengthen interventions across mobility management, socioeconomic support, and sexual health behaviors, applying COVID-19 lessons to mitigate MPX spread. Future research should integrate richer mobility data, individual-level risk assessments, and evolving epidemiological information to refine predictive models and guide targeted interventions.

- Data quality: Analyses rely on multiple open sources; although outliers were addressed and credible sources prioritized, findings depend on data accuracy. - COVID-19 reporting: As countries entered a post-COVID-19 phase, underreporting and limited accuracy of COVID-19 case data may introduce information bias. - Ecological design: Correlations are at the country level and may not imply causation; individual-level heterogeneity is not captured. - Modeling scope: The SEIR model includes mobility and age structure, but other factors may be important as more data become available; assumptions about non-travel of infected/recovered may not universally hold. - Endemic-country analysis: Focus was on imported countries during the 2022 outbreak; endemic country analyses were limited due to data constraints.