In late 2019, numerous cases of pneumonia with an unknown etiology were detected in the city of Wuhan, China. The causal agent was identified as a novel type of coronavirus and was named SARS-CoV-2 (1). The World Health Organization (WHO) officially designated the illness caused by SARS-CoV-2 as COVID-19 (coronavirus disease 2019). Subsequently, in March 2020 this emerging outbreak was declared a global pandemic (1, 2).

As an RNA virus, SARS-CoV-2 undergoes frequent mutations as part of its replication cycle. The high replication rates during the pandemic resulted in the emergence of new genotypes (3). The emergence of variants that had likely a greater effect in public health led the WHO to categorize them based on shared attributes and required public health actions. These categories include variants of concern (VOC), variants of interest (VOI) and variants under monitoring (VUM) (4). Notably, variants that were initially classified as VOC, like Alpha, Beta, Gamma, Delta and Omicron, were all reported in Central America (5, 6). Additionally, several lineages were first observed in countries within Central America and the Dominican Republic (7–10). These findings underscore the critical importance of genomic surveillance in this region to monitor the spread and evolution of the virus effectively.

The COVID-19 pandemic emphasized the significance of genomic surveillance, shedding light on the challenges associated with its implementation in the various public health systems. Consequently, since the beginning of the pandemic, government entities have made substantial investments toward the advancement and implementation of whole genome sequencing (WGS) (11, 12).

The implementation of an integrated genomic surveillance system during the pandemic has proven to be crucial for public health understanding and decision-making. This system has been instrumental in monitoring the real-time evolution of SARS-CoV-2 through the open exchange of data and online platforms like GISAID (Global Initiative on Sharing All Influenza Data, https://gisaid.org) (11, 12). By identifying and categorizing the various lineages of circulating viral diversity, this system has enabled the early detection of emerging variants before their widespread dissemination. Moreover, this monitoring made possible the linking of cases to clusters, tracing the origins of outbreaks, and identifying both national and international transmission routes. The knowledge gained about the different mutations present in circulating viruses was essential for the development of vaccines, treatments and diagnostic tests, as well as monitoring the impact of control measures (11, 12).

In Central America and the Dominican Republic, the progress made in genomic surveillance was strengthened by an effective collaboration model between the Pan American Health Organization (PAHO) and the Council of Ministers of Health of Central America (COMISCA). This collaboration aimed at enhancing capacities in the various countries of Central America and the Dominican Republic during the COVID-19 pandemic.

Thus, this study aimed to highlight the milestones in the strengthening of the genomic surveillance systems in the sub regions and to conduct a descriptive analysis of the lineages and circulating variants in Central America and the Dominican Republic from February 2020 to January 2023. This analysis is based on diverse SARS-CoV-2 genomes available in the GISAID database, sourced from material sequenced and shared by the public health laboratories within the subregion.

It is important to note that, although genomic and epidemiological data were jointly analyzed, the available metadata across countries did not consistently include key determinants such as vaccination coverage, prior infections, or the implementation and stringency of non-pharmaceutical interventions. As a result, statistical models assessing associations between circulating variants and reported cases or deaths could not incorporate these factors as covariates. This limitation inherently restricts the inferential scope of the models and should be considered when interpreting trends derived from the available data.

Over the years, outbreaks like severe acute respiratory syndrome (SARS; 2002–2023), influenza (2009) and Ebola (2013–2014) have highlighted the need for genomic surveillance to support public health surveillance systems (26). During the COVID-19 pandemic, genomics played a key role by enabling the tracking of SARS-CoV-2 variants and their spread, supporting the development of molecular diagnostics techniques, therapeutics and vaccines, fand informing decisions on the strengthening or easing of social distancing measures (27). This study did not assess whether genomic surveillance outputs directly impacted policy decisions, nor did it evaluate the timeliness of sequence generation and sharing. Turnaround times differed across countries, especially where external sequencing support was required, which may have limited the use of genomic data for real-time public health responses.

Interpretation of lineage frequencies must consider potential selection biases, as sequencing strategies were not systematic across countries. Differences in testing access, diagnostic algorithms, and sample triaging procedures likely influenced which samples were ultimately sequenced. These factors limit the comparability of lineage proportions across settings and should be considered when interpreting regional trends.

The recognition of the importance of genomic surveillance during the COVID-19 pandemic led to organizations such as PAHO (20) and COMISCA (21) to enhance genomic surveillance efforts across Central America and the Dominican Republic. A key objective of these strengthening programs was the development of local bioinformatics analysis capacity. As of 2025, many countries are still in the early stages of developing these skills.

In this context, INCIENSA in Costa Rica and ICGES in Panama were key players, as they led the implementation of SARS-CoV-2 genomic sequencing, as illustrated in Figure 1 (21). These efforts led to enhanced sequencing capacities among Central America and the Dominican Republic. As demonstrated in Figure 2, several countries with little to no sequenced samples throughout 2020 experienced a significant increase in sequencing activities in 2021, with many sustaining this progress into 2022.

As illustrated in Table 1, Nicaragua and Belize exhibit the highest percentages of sequenced COVID-19 cases. Nevertheless, as previously mentioned, Nicaragua's data may be biased due to national surveillance strategies and was therefore not considered for comparative purposes.

In contrast, Belize's elevated percentage of sequenced COVID-19 cases can be attributed to its substantially smaller population compared to the other countries analyzed in this study. Belize's population is approximately 11 times smaller than that of Panama, the country with the next smallest population in the region (22).

After excluding these outliers, a clearer assessment of the sequencing capacity in Central America and the Dominican Republic can be achieved. Table 1 shows that Costa Rica and Panama had higher percentages of sequenced COVID-19 cases (0.84 and 0.64%, respectively) than other countries in the region. This is expected, as both countries led regional sequencing efforts and had established local access to equipment and reagents (21). In contrast, the Dominican Republic, El Salvador, Guatemala and Honduras relied on shipment of samples to Panama or Costa Rica for sequencing (Figure 1), contributing to their lower percentages. Honduras showed particularly low coverage (0.06%), which may be associated with limited testing capacity, exacerbated by Hurricanes Eta and Iota and a concurrent dengue epidemic (28).

Previous studies suggest that sequencing at least 5% of all positive tests allows the detection of emerging strains with prevalence between 0.1 and 1.0% (29). However, none of the countries achieved this threshold (Table 1). Globally, only 6.8% of the countries worldwide achieved sequencing coverage ≥5%, while 45.5% sequenced less than 0.5% of confirmed cases (30). The low coverage observed in Central America and the Dominican Republic therefore reflects a broader global trend, particularly among low- and middle-income countries. This underscores the global disparities in SARS-CoV-2 genomic surveillance (30). Although sequencing coverage remained below the recommended 5% threshold (29) in the region, the genomic surveillance efforts still allowed the detection of circulating VOCs and recombinant lineages (Figures 3, 4). Lower coverage likely reduced sensitivity for early detention of novel variants. Sustained investment in sequencing capacity, standardized sampling, and improved turnaround times would strengthen future surveillance efforts.

Despite limited sequencing volume, the quality of the sequences was generally high. Across countries, the average completeness exceeded 98%, and most sequences met the quality threshold of ≥95% coverage and < 6% ambiguities. Although Nicaragua showed a lower proportion of high-quality sequences (72.2%), all other countries consistently surpassed 90%, indicating robust technical performance despite limited resources.

Understanding the genomic landscape of SARS-CoV-2 is essential for tracking its evolution and informing public health responses. Analysis of genotypes and their circulation patterns provides insights into how different variants emerge and spread within populations. A notable finding was the synchronous circulation of multiple lineages across the region, reflecting active dynamic transmission. Similar dynamics have been documented in Latin American countries (31–33), other continents (34, 35) and globally, largely facilitated by international travel as part of modern globalization (36).

These patters highlight the importance of robust communication and coordination between neighboring countries and those with strong travel and trade connections. Effective monitoring of circulating strains requires cross-border collaboration, particularly in highly interconnected regions. The frequency of different lineages over time and their geographic distribution, can be observed in Figure 2. In early stages of the pandemic, the B.1 lineage was detected throughout Central America and Dominican Republic. By early 2021, A 2.5 also emerged across these countries. Mid- 2021, saw the rise of Delta sublineages AY.100 and AY.113 (23), while early 2022, marked the widespread presence of Omicron sublineages, with BA.1.1 (2), becoming the first predominant sub lineage. This omicron trend continued through 2022 and early 2023, with recombinant Omicron sublineages such as XBB.1 (25), becoming prominent by late 2022 and early 2023. The synchronous presence of recombinant lineages, such as XBB.1, further underscores the regional interconnectedness and transmission dynamics, highlighting the need to have capacity to detect the locally generated new variants.

The temporal dynamics of lineage circulation in Central America and the Dominican Republic differed from global trends. Unlike in Europe and North America, where Alpha rapidly became dominant, in this region Alpha (B.1.1.7) did not reach predominance (37, 38). Its spread was constrained by the concurrent circulation of Gamma (P.1) (39), Mu (B.1.621) (40), and Lambda (C.37) (41), which were already established locally and likely competed for transmission advantage. These dynamics illustrate how regional epidemiological conditions can modulate the replacement patterns seen globally.

Throughout 2020, the predominant lineages were A.2, A.2.4 and B.1, the only variants exceeding 35 cases until December 2020 (Figures 3, 4). Although Alpha was first detected in late 2020 (37), it remained limited during early 2021. By mid-2021, Gamma (P.1) emerged as a predominant variant (39), accompanied by the co-circulation of Lambda (C.37) and Mu (B.1.621), both classified as VOIs (40, 41). This produced a more diverse variant landscape compared to other regions.

Delta sublineages (VOC) became predominant by mid-2021, rapidly replacing Gamma and other variants, following global patterns (42). Among Delta, AY.100 and AY.113 were the most frequent sublineages in late 2021, peaking at ~60% of sequenced cases, while additional AY lineages such as AY.25.1, B.1.617.2, AY.119, AY.3, AY.4, and AY.43 contributed to transient diversification (23, 37). A similar pattern was observed in Mexico (2).

By December 2021, Omicron represented ~40% of regional cases with BA.1.1 as the most frequent subvariant (24), increasing to ~90% by January 2022, consistent with global displacement of Delta (43–46). Early 2022 showed reduced lineage diversity (Figure 3), which later increased as multiple Omicron sublineages co-circulated.

Recombinant lineages also contributed to regional dynamics. XB—parented by B.1.634 and B.1.631—was the first recombinant in the region to exceed 35 cases, peaking mid-2021 (7, 47). XAM (BA.1.1/BA.2.9) (48) and XAF (BA.1/BA.2) (7) were most prevalent in the second quarter of 2022, with XAF showing notable presence in Panama. By late 2022 and early 2023, XBB.1 and XBB.1.5 became predominant, accounting for >50% of cases, consistent with their global emergence patterns (49–51).

Overall, these observations highlight that variant dynamics in the region were shaped by both global introductions and strong competition among locally circulating VOCs and VOIs, particularly during the Alpha-to-Gamma/Mu period. This emphasizes the importance of considering regional epidemiological contexts when interpreting global variant trajectories.

The trends illustrated in Figure 5 reveal a noticeable decoupling between the temporal dynamics of SARS-CoV-2 lineages and epidemiological outcomes. The introduction and rapid expansion of Omicron sublineages (e.g., BA.1.1, BA.2, XBB.1.5) in early 2022 coincided with a marked increase in reported case numbers (Figure 5b), whereas COVID-19-related deaths continued to decline steadily during the same period (Figure 5a). This divergence was supported by a low overall correlation (r = 0.10) between the average monthly lineage proportions and total deaths. Additionally, although regression models using negative binomial distributions identified weak but statistically significant associations—such as BA.2.9 with decreased case counts (p = 0.028) and XBB.1 with reduced mortality (p = 0.0148)—no individual lineage accounted for a substantial portion of the variability in either trend (Supplementary Table S2). These patterns suggest that factors beyond lineage predominance, such as increased vaccination coverage, accumulated population immunity, or changes in clinical management and public health strategies, likely had a more prominent role in shaping the epidemic curve during the Omicron-dominant period. Therefore, these associations should be interpreted with caution, as the models did not incorporate vaccination, prior infections, NPIs, or other contextual factors.

The partnership between PAHO, COMISCA and the participant countries in Central America and the Dominican Republic was key to building regional capacity. It enabled countries without laboratories to access genomic surveillance and participate in sequencing efforts. This combined effort fosters the democratization of genomic tools in low- and middle-income countries, enabling them to contribute with data that supports evidence-based decision-making both at regional and global levels.

However, challenges remain, particularly in sequencing capacity in countries like Honduras impacted by socioeconomic inequalities and limited access to public health systems (30). Addressing these gaps is essential to ensure robust responses to future pandemics or outbreaks. Additionally, several countries presented prolonged gaps in sequencing activity, particularly during the early stages of the pandemic. These gaps may be attributed to logistical constraints, limited laboratory infrastructure, lack of trained personnel, or resource limitations in public health systems. For example, Honduras and El Salvador reported very few sequences during key periods (28). These disparities not only reflect structural inequalities across the region but also limit the representativeness of regional genomic trends. Similar gaps have been reported globally, approximately 63% of SARS-CoV-2 sequences lacked age or sex information and over 95% lacked clinical data such as vaccination status or symptom history (52).

Furthermore, genomic surveillance data plays a crucial role in informing public health decisions, including the development of appropriate tests, vaccines and treatment strategies (30). This highlights the necessity for continued regional cooperation to effectively manage viral evolution and expand surveillance efforts to encompass other pathogens and antimicrobial resistance, which has seen a notable rise in recent years (30, 53). Investing in genomic surveillance will enhance our understanding of viral circulation dynamics and health systems impact. It also strengthens infectious disease control strategies and supports real-time intervention management (53). Sustained genomic surveillance is vital for preparedness against future health threats, emphasizing the need for ongoing collaboration among countries.

Vaccination efforts across Central America and the Dominican Republic may have influenced the dynamics of lineage circulation (6). Although this study did not assess vaccination coverage by country, it is plausible that higher vaccination rates helped reduce the spread or persistence of certain variants. Conversely, delays in vaccine rollout could have provided favorable conditions for the expansion of specific lineages. Future analyses integrating vaccination timelines and coverage data with genomic trends would provide valuable insights into the relationship between immunization and variant dynamics (54).

The genomic surveillance data obtained during the study period supported public health decision-making processes in the region. For instance, the detection of specific lineages contributed to the revision of travel advisories and the adjustment of entry requirements in some countries (36). Additionally, the sequencing results provided evidence to refine vaccination strategies and prioritize populations at higher risk (11). Although the short-term efforts were successful, a long-term surveillance strategy is essential. This includes sustained funding, regional laboratory networks, workforce training, and integration of genomic data into routine public health response systems (26, 30).

Regional mobility likely played a critical role in the introduction and spread of SARS-CoV-2 lineages (36). While the study did not include travel history metadata, the emergence of similar lineages in neighboring countries within a short time frame suggests transboundary movement of the virus (31). Countries with stronger international connectivity, such as Panama and Costa Rica, may have served as primary entry points for founder lineages (55). Additionally, the lack of detected VOCs, VOIs or VUMs in some countries may reflect gaps in sequencing coverage rather than true absence of circulation (30). This underscores the need to integrate mobility data and improve coordinated genomic surveillance across borders.

Moreover, irregular migration may have contributed to viral spread through unconventional routes. One such situation is the Darién Gap, a dense jungle corridor between South America and Panama. In 2022, the Panamanian government reported over 250,000 migrants crossing this area under precarious conditions, potentially increasing the region's epidemiological connectivity (56). In addition, seasonal and binational migration among Indigenous populations, such as the Ngäbe–Buglé communities residing along the Panama–Costa Rica border, may also play a role in regional disease dynamics. These communities frequently migrate for agricultural work, particularly during Costa Rica's coffee harvest, and often settle in towns near production areas. Many Ngäbe individuals are binational citizens who regularly access health services in Costa Rica, following routes that overlap with known northbound migratory pathways. These movements underscore the need for integrated, cross-border genomic surveillance strategies that account for the health vulnerabilities of highly mobile and underserved populations (57). However, this interpretation remains speculative, as the available data do not allow determination of whether mobility in these population groups had any measurable or disproportionate effect on the observed variant dynamics.

While several genomic surveillance studies have been conducted in Latin America (58–60), to our knowledge, this is the first study to describe the regional characteristics of the SARS-CoV-2 genome in Central America and the Dominican Republic. These findings provide critical public health insights by underscoring the need for equitable access to sequencing technologies and sustained regional collaboration. Such efforts are essential to effectively monitor viral evolution and inform evidence-based interventions in a region historically constrained by limited resources and infrastructure.

This study has several limitations. It relies on publicly available data with limited metadata, assumes that sequenced genomes accurately represent local and regional contexts, and does not account for country-specific factors such as diagnostic and surveillance investments, containment measures, or other relevant country-level indicators. Nonetheless, integrating regional genomic surveillance into national health systems could improve outbreak response times, enhance the detection of emerging variants, and enable more efficient allocation of scarce healthcare resources.

This overview of SARS-CoV-2 genomic surveillance in Central America and Dominican Republic highlights the critical role of the collaborative efforts between PAHO and COMISCA in enhancing regional sequencing capacity. By improving laboratory resources and fostering cooperation, countries effectively monitored key variants, including Delta and Omicron, demonstrating synchronous transmission dynamics across the region. The rise of recombinant variants emphasizes the ongoing evolution of the virus and the need to sustain genomic monitoring.

This collaborative model provides a robust framework for future public health crises, ensuring readiness to respond to emerging threats. Moving forward, countries should continue to build on these achievements, addressing opportunities for improvement in the sequencing capacity and promoting further collaborations to safeguard public health in the region.