---
title: "Serotype-specific dengue transmission intensity in Mexico (2016–2023): national modelling analysis"
id: "plos-medicine-1-overall-and-serotype-specific-dengue-virus-transmission-intensity-in-mexico"
canonical_url: "https://medichelpline.com/clinical-feed/plos-medicine-1-overall-and-serotype-specific-dengue-virus-transmission-intensity-in-mexico"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "PLOS Medicine"
source_url: "https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874"
published_at: "2026-09-03T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Serotype-specific dengue transmission intensity in Mexico (2016–2023): national modelling analysis
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-medicine-1-overall-and-serotype-specific-dengue-virus-transmission-intensity-in-mexico
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** PLOS Medicine
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874)
- **Published At:** 2026-09-03T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This study analysed 833,629 probable or confirmed dengue cases reported to Mexico’s National Epidemiological Surveillance System (SINAVE) between 2016 and 2023 to quantify transmission intensity across 27 states. - Researchers used established catalytic models and developed a new **serotype-specific** extension to estimate the **force of infection (FOI)** overall and for each dengue virus (**DENV**) serotype. - The analysis found substantial spatial, temporal, and serotype-specific heterogeneity in DENV transmission across Mexico during 2016–2023. - **DENV-1** and **DENV-2** showed historically high transmission intensity across much of Mexico. - **DENV-4** exhibited consistently low transmission intensity throughout the study period. - There was evidence of increasing **DENV-3** transmission intensity in some states in recent years, coinciding with large outbreaks. - Transmission intensity was generally higher in southern coastal and tropical regions, with higher estimates observed in the south in 2023; northern-central regions, especially high-altitude areas, had lower endemic transmission. - The models assume serotypes do not differ in their propensity to cause symptomatic disease and that observed serotype data are representative of circulating serotypes; the authors note these assumptions require validation. - The study highlights the value of extensive RT-PCR testing and new rapid diagnostics able to identify serotypes to improve surveillance and refine transmission estimates. - Aggregated data and code are publicly available on GitHub and Zenodo; individual-level line-list data for 2020–2023 are available from the Mexican Ministry of Health, while 2016–2019 data were obtained from INAI and are available on request. - The authors caution that heterogeneities in case reporting across states and over time may affect serotype-specific FOI estimates and should be explored in future work.
## Clinical Analysis & Structured Key Points
[ Skip to main content ](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#main-content) Advertisement * [plos.org](https://plos.org/) * [Create account](https://community.plos.org/registration/new) * [Sign in](https://journals.plos.org/user/secure/login?page=%2Fplosmedicine%2Farticle%3Fid%3D10.1371%2Fjournal.pmed.1004874) * * About * Browse * Publish * [](https://journals.plos.org/plosmedicine/ "PLOS Medicine") * Search [advanced search](https://journals.plos.org/plosmedicine/search) * Loading metrics Open Access Peer-reviewed Research Article # Overall and serotype-specific dengue virus transmission intensity in Mexico, 2016–2023: A modelling study of case-notification data * Oliver S. Simmons , Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing * E-mail: oliver.simmons22@imperial.ac.uk Affiliation MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0009-0004-9200-1517 ](https://orcid.org/0009-0004-9200-1517 "ORCID Registry") ⨯ * Anna Vicco, Roles Conceptualization, Formal analysis, Methodology, Software, Supervision, Visualization, Writing – review & editing Affiliation MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-6555-3090 ](https://orcid.org/0000-0002-6555-3090 "ORCID Registry") ⨯ * Ruth A. Martínez-Vega, Roles Conceptualization, Writing – review & editing Affiliation Facultad de Ciencias Médicas y la Salud, Universidad de Santander, Bucaramanga, Colombia [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-6477-334X ](https://orcid.org/0000-0002-6477-334X "ORCID Registry") ⨯ * José Ramos-Castañeda, Roles Conceptualization, Writing – review & editing Affiliation Centro de Investigaciones sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, México [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0003-3682-1938 ](https://orcid.org/0000-0003-3682-1938 "ORCID Registry") ⨯ * Ilaria Dorigatti Roles Conceptualization, Formal analysis, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing Affiliation MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0001-9959-0706 ](https://orcid.org/0000-0001-9959-0706 "ORCID Registry") ⨯ # Overall and serotype-specific dengue virus transmission intensity in Mexico, 2016–2023: A modelling study of case-notification data * Oliver S. Simmons, * Anna Vicco, * Ruth A. Martínez-Vega, * José Ramos-Castañeda, * Ilaria Dorigatti ![PLOS](https://journals.plos.org/resource/img/logo-plos-full-color.svg) x * Published: September 3, 2026 * * [Article](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874) * [Authors](https://journals.plos.org/plosmedicine/article/authors?id=10.1371/journal.pmed.1004874) * [Metrics](https://journals.plos.org/plosmedicine/article/metrics?id=10.1371/journal.pmed.1004874) * [Comments](https://journals.plos.org/plosmedicine/article/comments?id=10.1371/journal.pmed.1004874) * [Media Coverage](http://plos.altmetric.com/details/doi/10.1371/journal.pmed.1004874) * [Peer Review](https://journals.plos.org/plosmedicine/article/peerReview?id=10.1371/journal.pmed.1004874) * [Abstract](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#abstract0) * [Author summary](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#abstract1) * [Introduction](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#sec004) * [Methods](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#sec005) * [Results](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#sec016) * [Discussion](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#sec022) * [Supporting information](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#sec023) * [References](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#references) * [Reader Comments](https://journals.plos.org/plosmedicine/article/comments?id=10.1371/journal.pmed.1004874) * [Figures](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874) ## Abstract ### Background Mexico, and the Americas region more widely, have experienced increased dengue incidence in recent years, and there are concerns that the changing climate may enhance dengue virus (DENV) transmission in the future. Whilst previous studies have characterised spatial heterogeneities in the long-term average risk of DENV infection in Mexico, the extent to which DENV transmission changes year-to-year has not been investigated. Furthermore, the extent to which DENV’s four serotypes (DENV-1, DENV-2, DENV-3 and DENV-4) may differ in their transmissibility remains poorly characterised, both in Mexico and globally. ### Methods and findings In this study, we characterised the spatial and temporal variations in DENV transmission intensity, as defined by the force of infection, across 27 states in Mexico. We analysed annual dengue case data reported to the National Epidemiological Surveillance System (SINAVE) in Mexico between 2016 and 2023, which comprised 833,629 probable or confirmed cases, using established catalytic models and a new, serotype-specific extension of these models that characterises differences in the transmission intensity of the different serotypes. We found evidence of large spatial, temporal, and serotype-specific heterogeneities in transmission intensity across Mexico. Serotype-specific force of infection estimates suggest that DENV-1 and DENV-2 have historically circulated at high levels across Mexico, with DENV-4 showing a low transmission intensity throughout the study period. We found evidence of increasing DENV-3 transmission intensity across some states in recent years, coinciding with large outbreaks. The extent to which the serotype-specific transmission intensity estimates generated in this study are affected by potential heterogeneities in case reporting across states and through time remains to be validated in future studies. ### Conclusions This work quantifies serotype-specific differences in DENV transmission intensity using routinely collected case-notification data and demonstrates how extensive RT-PCR testing and new rapid diagnostic tests capable of discerning infecting serotypes can help to better understand the contributions of different serotypes to DENV transmission. The methods developed in this study contribute to the development of a better understanding of the past and current burden of dengue infection, which can help to refine assessments of the potential impact of existing and new interventions in future analyses. ## Author summary ### Why was this study done? * Dengue, caused by infection with dengue virus, is an increasing public health threat globally, and is a cause of particular concern in Mexico and the Americas, where outbreaks have intensified in recent years. * There are four serotypes of dengue virus, and due to the lack of serotype-specific data, modelling studies have traditionally assumed that the four serotypes are equally transmissible despite this hypothesis remaining to be validated. * Mexico is one of the few countries to publish individual-level data on reported dengue cases, including the serotype of cases (when available), which provides new opportunities to generate evidence around the transmission intensity of the circulating serotypes. ### What did the researchers do and find? * We applied mathematical models to analyse the data reported by disease surveillance, quantifying the intensity of dengue virus transmission in Mexico between 2016 and 2023. * We developed a new model to estimate the transmission intensity of each of the circulating dengue virus serotypes separately. * The intensity of dengue virus transmission varied by year, state, and serotype, with higher estimates obtained in the south of the country in 2023. ### What do these findings mean? * We find evidence of substantial heterogeneity in dengue virus transmission intensity by state, year and serotype, which implies that the immunity profile of the population across the country is highly heterogeneous too. * The methods developed in this paper can be applied to other countries, and the estimates can be used to inform the implementation of control interventions, surveillance strengthening, and public health decision-making. * The model developed in this study assumes that dengue virus serotypes do not differ in their propensity to cause symptomatic disease, and that the observed serotype-specific data are representative of the serotypes circulating in the population. To date, these assumptions remain to be validated in Mexico and globally. ## Figures ![Fig 7](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g007) ![Fig 1](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g001) ![Fig 2](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g002) ![Fig 3](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g003) ![Fig 4](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g004) ![Fig 5](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g005) ![Fig 6](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g006) ![Fig 7](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g007) ![Fig 1](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g001) ![Fig 2](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g002) ![Fig 3](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1004874.g003) **Citation:** Simmons OS, Vicco A, Martínez-Vega RA, Ramos-Castañeda J, Dorigatti I (2026) Overall and serotype-specific dengue virus transmission intensity in Mexico, 2016–2023: A modelling study of case-notification data. PLoS Med 23(9): e1004874. https://doi.org/10.1371/journal.pmed.1004874 **Academic Editor:** Peter MacPherson, University of Glasgow, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND **Received:** December 8, 2025; **Accepted:** June 9, 2026; **Published:** September 3, 2026 **Copyright:** © 2026 Simmons et al. This is an open access article distributed under the terms of the [Creative Commons Attribution License](http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. **Data Availability:** The aggregated data and code needed to run the models can be accessed through GitHub, via the URL , or through Zenodo, via . The individual-level data used to generate the aggregated data provided above are available partly publicly and partly upon request. Line-list dengue case data for 2020-2023 is available online from the Mexican Ministry of Health ( ). The data for 2016–2019 were obtained from the Instituto Nacional de Acceso a la Información (INAI, Mexico), reference number 330026924000362, and any interested party may request them via the National Transparency Platform at . Population data for Mexico from the 2015 intercensal survey and 2020 census are available publicly from INEGI at and . **Funding:** OSS, AV and ID acknowledge centre funding for the MRC Centre for Global Infectious Disease Analysis (reference MR/X020258/1), funded by the UK Medical Research Council (MRC, ). This UK funded award is carried out in the frame of the Global Health EDCTP3 Joint Undertaking. ID also acknowledges funding from Wellcome Trust ( ) (213494/Z/18/Z, 226072/Z/22/Z, 226727/Z/22/Z and 228185/Z/23/Z). The funders played no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. **Competing interests:** The authors have declared that no competing interests exist. **Abbreviations:** CAP, clinics associated with pharmacies; CFR, case fatality rate; DENV, dengue virus; DIC, deviance information criterion; FOI, force of infection; INAI, Instituto Nacional de Acceso a la Información; LOOIC, leave-one-out information criterion; PAHO, Pan American Health Organization; RECORD, Reporting of Studies Conducted Using Observational Routinely-Collected Data; RT-PCR, reverse transcription polymerase chain reaction; SINAVE, Sistema Nacional de Vigilancia Epidemiológica; WAIC, widely-applicable information criterion ## Introduction The annual number of suspected dengue cases in the Americas, whilst variable, has increased steadily since 2000 [[1](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref001)], with estimates suggesting that 16.7 (95% confidence interval [CI] [15.6, 17.7]) million infections and 7.6 (95% CI [4.8, 9.9]) million febrile cases occur on average each year in the region [[2](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref002)]. The principal vector of dengue virus (DENV), the mosquito _Aedes aegypti_ , thrives in urban areas, breeding in small containers of water, and an increasingly urban global population therefore puts a growing number of people at risk of the disease. Increases in temperature and changing rainfall patterns, direct results of climate change, already have and will continue to impact the global distribution of infection and disease in the future [[3](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref003),[4](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref004)], with currently inhospitable arid and temperate regions possibly becoming suitable to _Aedes_ mosquitoes, and therefore dengue. Changes in both urbanisation and climate are particularly acute in Mexico, where over 100 million people live in urban areas [[5](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref005),[6](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref006)]. Mexico’s dengue burden has historically been greater in coastal and tropical regions in the south of the country, where the disease is endemic or hyper-endemic, and lower in the northern-central part of the country corresponding roughly to the Mexican Altiplano, as transmission here is limited by the high altitude, especially in areas higher than 1,700m above sea level (though exceptions to these generalities exist) [[7](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref007),[8](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref008)]. Despite these limiting factors, Mexico reported approximately 278,000 cases of dengue in 2023, which represented the highest annual incidence in the country in the last decade (as recorded by the Pan American Health Organization (PAHO)), and the second highest number of cases in the Americas in 2023 after Brazil [[1](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref001)]. In 2024, dengue incidence in Mexico approximately doubled, with more than 558,000 cases reported to PAHO. Previous studies have suggested that the burden of dengue in Mexico may worsen further over the coming years due to climate change, although the extent and geographical distribution of any predicted change differs between models [[3](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref003),[9](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref009)]. DENV transmission in Mexico is currently highly cyclical, both on an annual basis, with cases peaking between August and November each year during the rainy season, and on a year-to-year basis, with large outbreaks occurring every 3–4 years [[1](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref001)]. This inter-annual pattern of dengue is most likely a result of the complex population immune profiles that result from infection with DENV [[10](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref010),[11](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref011)], which is made up of four, often co-circulating, serotypes denoted DENV-1, DENV-2, DENV-3 and DENV-4. Upon infection, each serotype confers long-term immunity to that serotype, and short-term immunity to heterologous serotypes, though estimates of the duration of this immunity vary [[12](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref012)]. This complex relationship between immunity and disease also makes evaluations of dengue’s disease burden difficult, and, due to differences in disease severity [[13](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref013)], the extent to which primary and post-primary (including tertiary and quaternary) infections are reported to surveillance can vary. Heterogeneities in the underreporting of cases across Mexico (as in any other country) and local differences in the sensitivity of dengue surveillance (driven, for instance, by differences in the historical trends of local DENV transmission) imply that the true burden of DENV infection is not necessarily reflected by the magnitude of the reported data [[7](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref007),[14](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref014)]. The burden of dengue can, however, be estimated from the age-distribution of the reported case data through mathematical models. An important measure of DENV’s transmission intensity is the rate at which susceptible people become infected, known as the force of infection (FOI). The FOI of DENV can be estimated using a class of mathematical models referred to as catalytic models, first used to model DENV transmission dynamics by Ferguson and colleagues [[15](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004874#pmed.1004874.ref015)], using either seroprevalence
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