Abstract
Two influenza A subtypes (H1N1 and H3N2) co-circulate and pose a serious disease burden globally. It is unclear about the extent of cross-protection between these two influenza A subtypes as well as the impact of cross-protection on influenza dynamics. Based on an evolution-driven mathematical transmission model, the interaction between H1N1 and H3N2 was explored based on monthly incidence data in the USA from the years 2012 to 2019. The results showed that significant cross-protection between H1N1 and H3N2 exists. Besides, the cross-protection for H1N1 from H3N2 is much stronger than the other way around. The results also show that cross-protection between H1N1 and H3N2 has substantial influence on the epidemics. The model was also validated in Germany, Austria and Norway. A forecasting framework was proposed based on the model with feasible accuracy for both retrospective and prospective forecasts of H1N1 and H3N2 in the USA. Our findings quantify and highlight the importance of cross-protection on the co-circulating of seasonal influenza A H1N1 and H3N2.
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Funding
This research was funded by Shenzhen Science and Technology Program under grant KQTD20180411143323605, National Natural Science Foundation of China under Grants 31970643 and 81961128002, the Guangdong Frontier and Key Tech Innovation Program under grants 2021A111112007, 2019B020228001 and 2019B111103001, the Natural Science Foundation of Guangdong Province, China, under grant 2021A1515011592.
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XD designed the study. GW, SL and FT collected the data, GW, BZ and SL built the model. GW performed the analysis. XD, GW, BZ, SL, YZ and DT interpreted the data. XD and GW prepared the manuscript. XD, GW, BZ, YZ and DT edited the paper. All authors reviewed and approved the submitted manuscript.
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Wang, G., Zhang, B., Liang, S. et al. Exploring the interaction of influenza A subtypes H1N1 and H3N2 based on an evolution-driven transmission model. Nonlinear Dyn 110, 933–944 (2022). https://doi.org/10.1007/s11071-022-07661-7
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DOI: https://doi.org/10.1007/s11071-022-07661-7