Additional considerations for assessing COVID-19 impact on dengue transmission.

In their multi-continent assessment of the impact of COVID-19-related restrictions on dengue incidence, Yuyang Chen and colleagues reported an astounding drop in dengue risk in 2020 attributable to public health and social measures during the pandemic (relative risk 0·01–0·17; p<0·01). Taking population immunity into account, the authors acknowledged how the unprecedented dengue burden of 2019 might have driven high immunity to dengue in 2020. Chen and colleagues also mentioned idiosyncrasies in the model that could not be explained. We would like to add possible considerations of (1) administrative delays and (2) genotype-replacement events driving the 2019 epidemics affecting conclusions drawn from the model.

On a much smaller, regional scale, we assessed how COVID-19 might have impacted dengue transmission in southeast Asia. Administrative delays from the COVID-19 burden resulted in under-reporting, delayed reporting, and no reporting from some areas given how taxed health-care systems were during this time. This fact alone might not complicate the model's conclusions, but if the case fatality rate is being used as a surrogate measure of under-reporting, 2020 would vary greatly from previous years, leading to an inflated interpretation of COVID-19 restrictions.

Second, the complicated interplay of dengue serotype-specific immunity contributes to the difficulty of predicting dengue virus outbreaks at local, subnational, or national levels. A recent study of data from Thailand revealed that as dengue virus evolves to evade host immunity, major epidemics result when a serotype strain becomes more antigenically similar to other serotypes than its own. The force of the invading strain can result in a selective sweep, reducing viral diversity with a subsequent drop in cases. Chen and colleagues added spatial random effects to account for the introduction of new dengue serotypes, and population immunity was labelled annual anomaly in the model. However, we would like to suggest to the authors that the greatest dengue year on record in 2019, in terms of incidence, be treated as unique in that it was probably fuelled by viral evolutionary events resulting in genotype replacements and might falsely augment the differential dengue virus burden between a higher-than-usual 6-year mean dengue incidence (inclusive of 2019) versus the comparison year of 2020. From an academic standpoint, we would be curious to see how the model would perform if the outlier year of 2019 were removed.

We appreciate the authors’ timely contribution to understand the multifaceted disease ecology of dengue coupled with human movement data in the context of COVID-19.

We declare no competing interests.