Superspreading Events Research Articles

Effectiveness of probabilistic contact tracing in epidemic containment: The role of superspreaders and transmission path reconstruction.

The recent COVID-19 pandemic underscores the significance of early stage nonpharmacological intervention strategies. The widespread use of masks and the systematic implementation of contact tracing strategies provide a potentially equally effective and socially less impactful alternative to more conventional approaches, such as large-scale mobility restrictions. However, manual contact tracing faces strong limitations in accessing the network of contacts, and the scalability of currently implemented protocols for smartphone-based digital contact tracing becomes impractical during the rapid expansion phases of the outbreaks, due to the surge in exposure notifications and associated tests. A substantial improvement in digital contact tracing can be obtained through the integration of probabilistic techniques for risk assessment that can more effectively guide the allocation of diagnostic tests. In this study, we first quantitatively analyze the diagnostic and social costs associated with these containment measures based on contact tracing, employing three state-of-the-art models of SARS-CoV-2 spreading. Our results suggest that probabilistic techniques allow for more effective mitigation at a lower cost. Secondly, our findings reveal a remarkable efficacy of probabilistic contact-tracing techniques in performing backward and multistep tracing and capturing superspreading events.

Epidemiologic Analysis of a Postelimination Measles Outbreak in Central Ohio, 2022-2023

Postelimination outbreaks threaten nearly a quarter century of measles elimination in the US. Understanding these dynamics is essential for maintaining the nation's measles elimination status. To examine the demographic characteristics and transmission dynamics of the 2022 to 2023 central Ohio measles outbreak. This cross-sectional study used electronic medical records and publicly available measles reports within an extensive central Ohio primary care network involving inpatient and outpatient settings. Participants included 90 children in Ohio with confirmed measles cases in 2022. The exposure of interest was confirmed measles cases in Ohio in 2022. This included 5 internationally imported cases and 85 locally acquired cases. The primary outcome involved documenting and analyzing confirmed measles cases in Ohio in 2022, focusing on demographic characteristics, immunization status, and transmission links in outbreak-related cases. This study analyzed 90 measles cases (47 [52.2%] male participants) in Ohio during 2022. Most participants self-identified as African or American Black (72 [80.0%]), with additional race categories including Asian, Hispanic, multirace (6 [6.7%]), White, and unknown (6 [6.7%]). Most participants were of Somali descent (64 [71.1%]), with additional ethnicity categories including American (16 [17.8%]), Guatemalan, Nepali, and unknown (6 [6.7%]). Participants were predominantly younger than 6 years (86 [95.5%]), unimmunized (89 [98.9%]), and resided in Franklin County, Ohio (83 [92.2%]). Prior to November 20, 2022, all cases occurred among unimmunized children of Somali descent in the Columbus area. Nosocomial superspreading events expanded the outbreak beyond the initially affected community. This cross-sectional study of measles cases in Ohio during 2022 found that the outbreak primarily affected unimmunized children of Somali descent, highlighting the necessity for culturally tailored public health strategies to maintain measles elimination in the US. These findings underscore the importance of implementing targeted interventions and enhancing community engagement to increase vaccination rates.

Host behaviour driven by awareness of infection risk amplifies the chance of superspreading events.

We demonstrate that heterogeneity in the perceived risks associated with infection within host populations amplifies chances of superspreading during the crucial early stages of epidemics. Under this behavioural model, individuals less concerned about dangers from infection are more likely to be infected and attend larger sized (riskier) events, where we assume event sizes remain unchanged. For directly transmitted diseases such as COVID-19, this leads to infections being introduced at rates above the population prevalence to those events most conducive to superspreading. We develop an interpretable, computational framework for evaluating within-event risks and derive a small-scale reproduction number measuring how the infections generated at an event depend on transmission heterogeneities and numbers of introductions. This generalizes previous frameworks and quantifies how event-scale patterns and population-level characteristics relate. As event duration and size grow, our reproduction number converges to the basic reproduction number. We illustrate that even moderate levels of heterogeneity in the perceived risks of infection substantially increase the likelihood of disproportionately large clusters of infections occurring at larger events, despite fixed overall disease prevalence. We show why collecting data linking host behaviour and event attendance is essential for accurately assessing the risks posed by invading pathogens in emerging stages of outbreaks.

Impact of a large-scale event on SARS-CoV-2 cases and hospitalizations in the Netherlands, carnival seasons 2022 and 2023

ObjectivesThe COVID-19 pandemic highlights the importance of understanding facilitators for disease transmission. Events such as Carnival, characterized by large gatherings and extensive social interactions, have the potential to become ‘super spreading events' for respiratory infections. This paper aims to assess the impact of large gatherings on virus transmission, providing crucial insights for the development of effective public health strategies. Study designAn ecological study was performed. MethodsThe age-standardized number of COVID-19 cases reported in 2022, stratified by age (under 60 and 60+ years) was compared countrywide for Dutch provinces where Carnival was celebrated versus those where it was not. Additionally, we compared standardized hospitalization rates in 2022 and 2023 for both areas. ResultsCountrywide, 2,278,431 COVID-19 cases were reported between 06-02-2022 and 10-04-2022. Daily incidence increased after Carnival, peaking at 803 per 100,000 inhabitants for under 60s in carnival provinces and 368 in non-carnival provinces. For individuals 60+ daily incidence peaked at 396 in carnival provinces and 247 in non-carnival provinces. Over the 10 weeks following the start of Carnival, the carnival provinces demonstrated a 15 % (2022) 17 % (2023) higher hospitalization rate compared to non-carnival provinces. ConclusionsThe peak in cases and hospitalizations in regions actively celebrating Carnival compared to the rest of the Netherlands qualifies Carnival as a ‘super-spreading’ event. Our findings underscore the elevated risk of respiratory infections associated with large gatherings, advocating guided policies, including transparent risk communication and healthcare preparedness.

Sudan virus disease super-spreading, Uganda, 2022

BackgroundOn 20 September 2022, Uganda declared its fifth Sudan virus disease (SVD) outbreak, culminating in 142 confirmed and 22 probable cases. The reproductive rate (R) of this outbreak was 1.25. We described persons who were exposed to the virus, became infected, and they led to the infection of an unusually high number of cases during the outbreak.MethodsIn this descriptive cross-sectional study, we defined a super-spreader person (SSP) as any person with real-time polymerase chain reaction (RT-PCR) confirmed SVD linked to the infection of ≥ 13 other persons (10-fold the outbreak R). We reviewed illness narratives for SSPs collected through interviews. Whole-genome sequencing was used to support epidemiologic linkages between cases.ResultsTwo SSPs (Patient A, a 33-year-old male, and Patient B, a 26-year-old male) were identified, and linked to the infection of one probable and 50 confirmed secondary cases. Both SSPs lived in the same parish and were likely infected by a single ill healthcare worker in early October while receiving healthcare. Both sought treatment at multiple health facilities, but neither was ever isolated at an Ebola Treatment Unit (ETU). In total, 18 secondary cases (17 confirmed, one probable), including three deaths (17%), were linked to Patient A; 33 secondary cases (all confirmed), including 14 (42%) deaths, were linked to Patient B. Secondary cases linked to Patient A included family members, neighbours, and contacts at health facilities, including healthcare workers. Those linked to Patient B included healthcare workers, friends, and family members who interacted with him throughout his illness, prayed over him while he was nearing death, or exhumed his body. Intensive community engagement and awareness-building were initiated based on narratives collected about patients A and B; 49 (96%) of the secondary cases were isolated in an ETU, a median of three days after onset. Only nine tertiary cases were linked to the 51 secondary cases. Sequencing suggested plausible direct transmission from the SSPs to 37 of 39 secondary cases with sequence data.ConclusionExtended time in the community while ill, social interactions, cross-district travel for treatment, and religious practices contributed to SVD super-spreading. Intensive community engagement and awareness may have reduced the number of tertiary infections. Intensive follow-up of contacts of case-patients may help reduce the impact of super-spreading events.

Global Re-emergence of Monkeypox: A Synoptic Review

AbstractAs the coronavirus disease 2019 pandemic continues to rage, the unprecedented manifold increase in monkeypox (mpox) cases throughout the world is raising qualms about a possible pandemic. As of January 2024, the disease has been reported in around 116 countries, with nearly 92,500 confirmed cases and 170 deaths. In this mini-review, we have endeavored to cover multiple aspects of the mpox disease. Mpox virus is an enveloped double-stranded DNA virus that belongs to the Orthopoxvirus genus. The disease is endemic in certain African countries. Until recently, however, the disease was rarely reported in Europe and the United States. In contrast to the previous outbreaks outside Africa, reported cases in the 2022 outbreak did not travel to the endemic areas. Superspreading events at mass gatherings, multiple-partner sexual encounters, and international travel were major drivers of the recent global outbreak of mpox. The 2022 mpox virus may have undergone accelerated evolution. It diverges from the related 2018 to 2019 viruses by around 50 single-nucleotide polymorphisms, some of which brought about amino acid changes in immunogenic surface glycoprotein B21. Differential diagnosis for mpox could be quite challenging since it can masquerade as a wide variety of illnesses. Worse still, some patients may be asymptomatic or show subtle symptoms. The infection is confirmed by conventional or real-time polymerase chain reaction on lesion material. Although there is no specific therapy approved for mpox infections, two antivirals (tecovirimat and brincidofovir) and vaccinia immune globulin may be used. Vaccines also provide protection against mpox when properly administered prior to exposure. Finally, the implementation of preventive measures is of paramount importance, especially in regions where mpox transmission is widespread and among high-risk populations.

A study of growth of COVID-19 with super-spreaders using the modified SIR model including iceberg phenomenon

This paper explores the dynamics of COVID-19 transmission, particularly focusing on super-spreaders, through the lens of the SIR model. The model comprises six compartments representing susceptible, exposed, symptomatic infected, super-spreader, asymptomatic infected, and recovered individuals. Utilizing a set of non-linear, interdependent differential equations, we numerically solve for model parameters to examine the influence of super-spreaders on infection spread within the population. We calculate the basic reproduction number (R0) and discuss the stability of disease-free equilibrium. Our findings underscore the significant role played by super-spreaders and asymptomatic individuals in disease dissemination. Drawing on the epidemiological concept of the iceberg phenomenon, we offer insights into super-spreader events (SSEs) in India and their ramifications.

Host and viral determinants of airborne transmission of SARS-CoV-2 in the Syrian hamster

It remains poorly understood how SARS-CoV-2 infection influences the physiological host factors important for aerosol transmission. We assessed breathing pattern, exhaled droplets, and infectious virus after infection with Alpha and Delta variants of concern (VOC) in the Syrian hamster. Both VOCs displayed a confined window of detectable airborne virus (24–48 hr), shorter than compared to oropharyngeal swabs. The loss of airborne shedding was linked to airway constriction resulting in a decrease of fine aerosols (1–10 µm) produced, which are suspected to be the major driver of airborne transmission. Male sex was associated with increased viral replication and virus shedding in the air. Next, we compared the transmission efficiency of both variants and found no significant differences. Transmission efficiency varied mostly among donors, 0–100% (including a superspreading event), and aerosol transmission over multiple chain links was representative of natural heterogeneity of exposure dose and downstream viral kinetics. Co-infection with VOCs only occurred when both viruses were shed by the same donor during an increased exposure timeframe (24–48 hr). This highlights that assessment of host and virus factors resulting in a differential exhaled particle profile is critical for understanding airborne transmission.

Host and viral determinants of airborne transmission of SARS-CoV-2 in the Syrian hamster.

It remains poorly understood how SARS-CoV-2 infection influences the physiological host factors important for aerosol transmission. We assessed breathing pattern, exhaled droplets, and infectious virus after infection with Alpha and Delta variants of concern (VOC) in the Syrian hamster. Both VOCs displayed a confined window of detectable airborne virus (24-48 hr), shorter than compared to oropharyngeal swabs. The loss of airborne shedding was linked to airway constriction resulting in a decrease of fine aerosols (1-10 µm) produced, which are suspected to be the major driver of airborne transmission. Male sex was associated with increased viral replication and virus shedding in the air. Next, we compared the transmission efficiency of both variants and found no significant differences. Transmission efficiency varied mostly among donors, 0-100% (including a superspreading event), and aerosol transmission over multiple chain links was representative of natural heterogeneity of exposure dose and downstream viral kinetics. Co-infection with VOCs only occurred when both viruses were shed by the same donor during an increased exposure timeframe (24-48 hr). This highlights that assessment of host and virus factors resulting in a differential exhaled particle profile is critical for understanding airborne transmission.

The Impact of Urban Scaling Structure on the Local-Scale Transmission of COVID-19: A Case Study of the Omicron Wave in Hong Kong Using Agent-Based Modeling

Superspreading events underscore the uneven distribution of COVID-19 transmission among individuals and locations. These heterogenous transmission patterns could stem from human mobility, yet the underlying mechanisms are still not fully understood. Here, we employ an agent-based model incorporating urban scaling structure to simulate fine-grained mobility and the human-to-human transmission process. Our results reveal that not only the quantity but also the scaling structure of mobility profoundly influences local transmission risk. Urban scaling structure is characterized by a widely found power-law scaling distribution of mobility volumes across different locations. By integrating this structure, our model fits reasonably well with empirical Omicron data at various spatial scales in Hong Kong. Further analyses show a positive association between the scaling index, representing the location’s importance within the structure, and local transmission risks among urban areas as well as the likelihood of becoming superspreaders among local visitors. This implies that urban scaling structure could offer the first-mover advantage to a minority of places and individuals to infect earlier and thus infect more. This study brings important insights for the transmission dynamics of COVID-19 and similar diseases, highlighting the role of urban scaling structure in influencing local transmission risks and superspreading events.

HPAIV outbreak triggers short-term colony connectivity in a seabird metapopulation

Disease outbreaks can drastically disturb the environment of surviving animals, but the behavioural, ecological, and epidemiological consequences of disease-driven disturbance are poorly understood. Here, we show that an outbreak of High Pathogenicity Avian Influenza Virus (HPAIV) coincided with unprecedented short-term behavioural changes in Northern gannets (Morus bassanus). Breeding gannets show characteristically strong fidelity to their nest sites and foraging areas (2015–2019; n = 120), but during the 2022 HPAIV outbreak, GPS-tagged gannets instigated long-distance movements beyond well-documented previous ranges and the first ever recorded visits of GPS-tagged adults to other gannet breeding colonies. Our findings suggest that the HPAIV outbreak triggered changes in space use patterns of exposed individuals that amplified the epidemiological connectivity among colonies and may generate super-spreader events that accelerate disease transmission across the metapopulation. Such self-propagating transmission from and towards high density animal aggregations may explain the unexpectedly rapid pan-European spread of HPAIV in the gannet.

Epidemic modelling requires knowledge of the social network

‘Compartmental models’ of epidemics are widely used to forecast the effects of communicable diseases such as COVID-19 and to guide policy. Although it has long been known that such processes take place on social networks, the assumption of ‘random mixing’ is usually made, which ignores network structure. However, ‘super-spreading events’ have been found to be power-law distributed, suggesting that the underlying networks may be scale free or at least highly heterogeneous. The random-mixing assumption would then produce an overestimation of the herd-immunity threshold for given R 0; and a (more significant) overestimation of R 0 itself. These two errors compound each other, and can lead to forecasts greatly overestimating the number of infections. Moreover, if networks are heterogeneous and change in time, multiple waves of infection can occur, which are not predicted by random mixing. A simple SIR model simulated on both Erdős–Rényi and scale-free networks shows that details of the network structure can be more important than the intrinsic transmissibility of a disease. It is therefore crucial to incorporate network information into standard models of epidemics.

Transmission chains of the first local outbreak cause by Delta VariantB.1.617.2 COVID-19 in Guangzhou, Southern China

BackgroundThe first local outbreak of Delta Variant B.1.617.2 COVID-19 of China occurred in Guangzhou city, south China, in May 2021. This study analyzed the transmission chains and local cluster characteristics of this outbreak, intended to provide information support for the development and adjustment of local prevention and control strategies.MethodsThe transmission chains and local cluster characteristics of 161 local cases in the outbreak were described and analyzed. Incubation period, serial interval and generation time were calculated using the exact time of exposure and symptom onset date of the cases. The daily number of reported cases and the estimated generation time were used to estimate the effective reproduction number (Rt).ResultsWe identified 7 superspreading events who had more than 5 next generation cases and their infected cases infected 70.81%(114/161) of all the cases transmission. Dining and family exposure were the main transmission routes in the outbreak, with 29.19% exposed through dining and 32.30% exposed through family places. Through further analysis of the outbreak, the estimated mean incubation period was 4.22 (95%CI: 3.66–4.94) days, the estimated mean generation time was 2.60 (95%CI: 1.96–3.11) days, and the estimated Rt was 3.29 (95%CI: 2.25–5.07).ConclusionsClassification and dynamically adjusted prevention and control measures had been carried out according to analysis of transmission chains and epidemical risk levels, including promoting nucleic acid screening at different regions and different risk levels, dividing closed-off area, controlled area according to the risk of infection, raising the requirements of leaving Guangzhou. By the above control measures, Guangzhou effectively control the outbreak within 28 days without implementing a large-scale lockdown policy.

The Effect of Singers' Masks on the Impulse Dispersion of Aerosols During Singing.

During the Covid-19 pandemic, singing activities were restricted due to several super-spreading events that have been observed during rehearsals and vocal performances. However, it has not been clarified how the aerosol dispersion, which has been assumed to be the leading transmission factor, could be reduced by masks which are specially designed for singers. Twelve professional singers (10 of the Bavarian Radio-Chorus and two freelancers, seven females and five males) were asked to sing the melody of the ode of joy of Beethoven's 9th symphony "Freude schöner Götterfunken, Tochter aus Elisium" in D-major without masks and afterwards with five different singers' masks, all distinctive in their material and proportions. Every task was conducted after inhaling the basic liquid from an e-cigarette. The aerosol dispersion was recorded by three high-definition video cameras during and after the task. The cloud was segmented and the dispersion was analyzed for all three spatial dimensions. Further, the subjects were asked to rate the practicability of wearing the tested masks during singing activities using a questionnaire. Concerning the median distances of dispersion, all masks were able to decrease the impulse dispersion of the aerosols to the front. In contrast, the dispersion to the sides and to the top was increased. The evaluation revealed that most of the subjects would reject performing a concert with any of the masks. Although, the results exhibit that the tested masks could be able to reduce the radius of aerosol expulsion for virus-laden aerosol particles, there are more improvements necessary to enable the practical implementations for professional singing.

Superspreading of SARS-CoV-2 at a choir rehearsal in Finland-A computational fluid dynamics view on aerosol transmission and patient interviews.

COVID-19 pandemic has highlighted the role of aerosol transmission and the importance of superspreading events. We analyzed a choir rehearsal in November 2020, where all participants, except one who had recently earlier recovered from COVID-19, were infected. We explore the risk factors for severe disease in this event and model the aerosol dispersion in the rehearsal room. Characteristics of participants were collected by interviews and supplemented with patient records. A computational simulation of aerosol distribution in the rehearsal room and the efficacy of potential safety measures was conducted using the Large-Eddy Simulation approach. Infection risk was studied by analyzing quanta emission and exposure with the Wells-Riley equation. The simulation showed that airborne transmission likely explains this mass contagion event. Every singer was exposed to the virus in only 5 min from the beginning of the rehearsal, and maximum concentration levels were reached at 20 min the concentration levels started to approach a steady state after 20 min. Although concentration differences existed in the room, risk levels near (1 m) and far (5 m) from the aerosol source were similar for certain singers. Modeling indicated infection risk levels of 70-100% after one hour; the risk would have been considerably reduced by wearing high-filtration respirators. Age and pre-existing comorbidities predicted more severe disease. The high incidence of illness may be partly attributed to the relatively high median age of individuals. Additionally, those admitted to the hospital had multiple underlying health conditions that predispose them to more severe disease. Airborne transmission and indoor space can explain this mass exposure event. High-filtration respirators could have prevented some infections. The importance of safety distances diminishes the longer the indoor event. The concept of safety distance is challenging, as our study suggests that long range airborne transmission may occur in indoor events with extended duration. We encourage informing the public, especially persons at risk, of safety measures during epidemics.

Ventilation and disease monitoring of indoor spaces and public transportation using an NDIR sensor network

With the COVID-19 pandemic still ongoing, there is a need to ensure that people are not subjected to the risk of getting infected with the disease. Since COVID-19 is airborne, engineering controls must be provided to monitor and mitigate the spread of the disease in the air. One of the measures is to ensure proper ventilation within indoor spaces where superspreader events were previously documented in poorly ventilated spaces. CO2 levels reflect the rate at which the used air within is replaced and, therefore, can be used as a proxy for COVID-19 risk. This study developed economical CO2 monitors which are deployed across indoor spaces and public transportation, such as air-conditioned jeepneys, to communicate the risk. Using the least squares method on the first-order ODE of mass balance, a multivariate method is devised for deriving the occupancy and the ventilation rate from the recorded CO2 levels. Using the multivariate method, the ventilation rates of different indoor spaces are determined and used for the subsequent computations using the Wells–Riley model to derive the respective infection risk, particularly of COVID-19.

Unravelling the effect of New Year’s Eve celebrations on SARS-CoV-2 transmission

Public holidays have been associated with SARS-CoV-2 incidence surges, although a firm link remains to be established. This association is sometimes attributed to events where transmissions occur at a disproportionately high rate, known as superspreading events. Here, we describe a sudden surge in new cases with the Omicron BA.1 strain amongst higher education students in Belgium. Contact tracers classed most of these cases as likely or possibly infected on New Year's Eve, indicating a direct trigger by New Year celebrations. Using a combination of contact tracing and phylogenetic data, we show the limited role of superspreading events in this surge. Finally, the numerous simultaneous transmissions allowed a unique opportunity to determine the distribution of incubation periods of the Omicron strain. Overall, our results indicate that, even under social restrictions, a surge in transmissibility of SARS-CoV-2 can occur when holiday celebrations result in small social gatherings attended simultaneously and communitywide.

Data modeling COVID-19 patients in Thailand: data mining techniques

This study aimed to investigate the characteristics of COVID-19 patients in Thailand and develop a data model for analyzing these characteristics. A total of 1,888,941 cases from the Thailand Department of Disease Control website from January 12, 2020, to October 29, 2021, were analyzed, and 20,110 cases were selected for further analysis. The two-step cluster analysis method was used to cluster the data according to four variables: nationality, occupation, patient type, and risk groups. The results showed the presence of three groups of COVID-19 patients. Group 1 consisted of 5,883 workers in trade and service occupations who had contact with the public and were either Thai nationals or from abroad. Group 2 was the largest cluster, consisting of 7,420 migrant workers classified as foreigners and working in industrial settings. Group 3 consisted of 6,870 cases of indirect transmission, with individuals in this group infected through close contact with family members or individuals in the first two groups. This clustering approach offers valuable insights for pandemic management, aiding in identifying high-risk groups and developing tailored interventions. In future outbreaks with similar characteristics, such as airborne transmission, contact infection, or super spreader events, our model can serve as a valuable tool for devising effective management plans and countermeasures. In conclusion, this study emphasizes the significance of cluster analysis in understanding the dynamics of COVID-19 transmission and highlights its potential for informing effective pandemic management strategies. It also outlines promising avenues for further research to enhance our knowledge of COVID-19's impact on specific populations and inform future public health efforts.

Investigation of an international water polo tournament in Czechia as a potential source for early introduction of the SARS-CoV-2 Omicron variant into Belgium, Switzerland and Germany, November 2021.

BackgroundThe earliest recognised infections by the SARS-CoV-2 Omicron variant (Pango lineage B.1.1.529) in Belgium and Switzerland suggested a connection to an international water polo tournament, held 12-14 November 2021 in Brno, Czechia.AimTo study the arrival and subsequent spread of the Omicron variant in Belgium and Switzerland, and understand the overall importance of this international sporting event on the number of infections in the two countries.MethodsWe performed intensive forward and backward contact tracing in both countries, supplemented by phylogenetic investigations using virus sequences of the suspected infection chain archived in public databases.ResultsThrough contact tracing, we identified two and one infected athletes of the Belgian and Swiss water polo teams, respectively, and subsequently also three athletes from Germany. In Belgium and Switzerland, four and three secondary infections, and three and one confirmed tertiary infections were identified. Phylogenetic investigation demonstrated that this sporting event played a role as the source of infection, but without a direct link with infections from South Africa and not as a superspreading event; the virus was found to already be circulating at that time in the countries involved.ConclusionThe SARS-CoV-2 Omicron variant started to circulate in Europe several weeks before its identification in South Africa on 24 November 2021. Accordingly, it can be assumed that travel restrictions are usually implemented too late to prevent the spread of newly detected SARS-CoV-2 variants to other regions. Phylogenetic analysis may modify the perception of an apparently clear result of intensive contact tracing.

Geoepidemiological perspective on COVID-19 pandemic review, an insight into the global impact.

The COVID-19 pandemic showed major impacts, on societies worldwide, challenging healthcare systems, economies, and daily life of people. Geoepidemiology, an emerging field that combines geography and epidemiology, has played a vital role in understanding and combatting the spread of the virus. This interdisciplinary approach has provided insights into the spatial patterns, risk factors, and transmission dynamics of the COVID-19 pandemic at different scales, from local communities to global populations. Spatial patterns have revealed variations in incidence rates, with urban-rural divides and regional hotspots playing significant roles. Cross-border transmission has highlighted the importance of travel restrictions and coordinated public health responses. Risk factors such as age, underlying health conditions, socioeconomic factors, occupation, demographics, and behavior have influenced vulnerability and outcomes. Geoepidemiology has also provided insights into the transmissibility and spread of COVID-19, emphasizing the importance of asymptomatic and pre-symptomatic transmission, super-spreading events, and the impact of variants. Geoepidemiology should be vital in understanding and responding to evolving new viral challenges of this and future pandemics.