Published Aug 01, 2026 | 9:00 AM ⚊ Updated Aug 01, 2026 | 9:00 AM
Beyond vaccines, the authors believe the surveillance network could transform dengue forecasting in India.
Synopsis: An ICMR nationwide study found DENV-2 is the dominant dengue serotype across South India, while multiple dengue strains are circulating simultaneously across India. Researchers warn that concurrent infections may increase disease severity and stress that continuous molecular surveillance is essential for outbreak prediction and guiding future dengue vaccine introduction.
DENV-2 has emerged as the predominant dengue virus serotype across southern India, but a first-of-its-kind nationwide molecular surveillance study has found that multiple dengue strains are circulating simultaneously across the country, a trend researchers say could increase the risk of severe disease and shape India’s future dengue vaccination strategy.
The study, conducted by the Indian Council of Medical Research (ICMR) through its Virus Research and Diagnostic Laboratory (VRDL) network, analysed 6,889 laboratory-confirmed dengue samples collected from 45 laboratories across 25 States and Union Territories between May 2023 and May 2025. It is among the largest coordinated efforts to map dengue serotypes across India using a standardised testing protocol.
Researchers found that DENV-2 accounted for 51 percent of all infections, making it the dominant serotype nationwide. It was followed by DENV-3 (13 percent), DENV-1 (7 percent) and DENV-4 (1 percent). Around 7 percent of patients were infected with two or more dengue serotypes simultaneously, while 21 percent of tested samples did not yield a detectable serotype despite testing positive for dengue infection.
For South India, the findings provide a clearer picture of circulating strains than previous regional studies.
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The surveillance found DENV-2 to be the predominant serotype across all southern states included in the study, accounting for more than half of all detected infections in Andhra Pradesh, Karnataka, Kerala, Telangana and Puducherry. Tamil Nadu also recorded DENV-2 as the leading serotype, although the state had a more balanced distribution of circulating strains than the rest of the South.
In Tamil Nadu, DENV-2 accounted for about 42 percent of infections, while DENV-1 and DENV-3 each contributed around 29 percent, making it the only southern state with substantial circulation of three major serotypes. DENV-4 was not detected in the state during the study period.
In Telangana, DENV-2 constituted roughly 60-65 percent of infections, with the remaining 35-40 percent caused by DENV-3. No DENV-1 or DENV-4 infections were detected at the participating study site.
Andhra Pradesh reported around 60 percent DENV-2, followed by about 15 percent DENV-1, 10-15 percent DENV-3, with the remaining samples comprising concurrent infections and undetectable serotypes. Karnataka and Kerala showed a similar pattern, with DENV-2 accounting for nearly 60 percent of infections, followed by smaller proportions of DENV-1 and DENV-3. Puducherry also recorded DENV-2 as the dominant strain, representing about 60 percent of infections.
Overall, the findings indicate that while DENV-2 is driving dengue transmission across South India, states such as Tamil Nadu are experiencing substantial co-circulation of DENV-1 and DENV-3, highlighting regional differences in dengue epidemiology that could influence outbreak patterns and future vaccine strategies.
One of the study’s most significant findings was the growing burden of concurrent infections.
Among the 6,889 samples analysed, 485 patients, or approximately 7 percent, were infected with more than one dengue serotype at the same time. Depending on the state, concurrent infections ranged from 0 percent to 21 percent. The most common co-infection involved DENV-2 and DENV-3, accounting for 57 percent of all multiple-serotype infections, followed by DENV-1 with DENV-2 and DENV-3 together.
The authors found that patients with concurrent infections were more likely to develop thrombocytopenia (low platelet counts), hemorrhagic manifestations and arthralgia, compared with those infected by a single serotype.
Although the researchers cautioned that their findings need validation through prospective clinical studies, they said the observations suggest that simultaneous infection with multiple dengue serotypes may contribute to more severe disease.
The study noted that evidence linking concurrent infections to disease severity has remained inconsistent globally, but its findings add to growing concerns as India witnesses increasing hyper-endemic transmission.
The researchers said India has lacked harmonised nationwide data on dengue serotypes despite carrying one of the world’s largest dengue burdens.
According to the study, India contributes nearly 34 percent of the global burden of symptomatic dengue infections, yet most previous serotype studies have been restricted to individual cities or states, making it difficult to understand how circulating strains change over time and across regions.
Explaining the importance of the surveillance, the authors wrote:
“Molecular surveillance of dengue serotypes at regular intervals is critical for understanding serotype transmission dynamics and their burden on public health.”
They added that earlier studies, though valuable, “were confined to smaller geographies” and “were not representative of temporal patterns,” limiting their usefulness for national planning.
The present surveillance, they said, demonstrates how India’s VRDL network can generate geographically representative data capable of supporting future outbreak prediction.
“The enhanced testing capabilities at the site laboratories also establishes a robust platform for responding to future dengue epidemics, which pose a significant healthcare burden due to climate change, spread of vector mosquitoes and rapid urbanization,” the authors wrote.
The researchers further noted that expanding surveillance from the current 45 laboratories to all 165 VRDLs could improve data granularity and support local outbreak prediction models.
The findings come at a time when India is moving closer to introducing dengue vaccines.
Currently, Qdenga, a live attenuated tetravalent vaccine, has recently been approved for import and sale in India, while the indigenous vaccine candidate DengiAll is undergoing Phase III clinical trials.
The researchers say understanding which serotypes circulate in different parts of the country is becoming increasingly important because vaccine performance differs against individual dengue serotypes.
They wrote: “Continuous monitoring of circulating serotypes of dengue virus remains crucial for public health decisions regarding dengue vaccine introduction in the regional immunization program.”
The study added that periodic surveillance would allow health authorities to detect shifts in dominant serotypes resulting from migration, climate change, introduction of new strains and declining population immunity, all of which could influence vaccine effectiveness and outbreak severity.
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Beyond vaccines, the authors believe the surveillance network could transform dengue forecasting in India.
They pointed out that predicting dengue outbreaks remains difficult because disease transmission depends on numerous factors, including mosquito density, climate, population immunity and the combination of circulating serotypes.
The study says the nationwide molecular surveillance platform can generate the long-term data needed for reliable prediction models.
“Our preliminary study highlights the potential utility offered by the robust VRDL network platform to generate long-term, granular data regarding dynamics of DENV circulation in different parts of the country; which can be further used to develop reliable predictive models for epidemic prediction and healthcare burden assessment,” the authors wrote.
However, they argue that molecular surveillance alone is not enough.
“While molecular surveillance of dengue serotypes and genotypes can provide a surrogate indication of dengue transmission dynamics, an integrated approach combining serological, entomological, spatio-temporal, and climate data shall be more effective in developing reliable prediction models,” the authors said, adding that artificial intelligence-based forecasting tools could further improve public health preparedness.
