💡What are the implications? Ans: Social contact structure can affect the impact of PCVs and should be taken into consideration when estimating vaccine impact! (6/6)
🚨New paper alert: Sharing another latest study from our lab, "Assessing the effect of social contact structure on the impact of pneumococcal conjugate vaccines." https://t.co/C0dCTISJih
Read the 🧵to find out more! (1/6)
🔍 We found that varying the social contact matrix alone led to a range of time-to-elimination (3.8-6 years). We further found that such variation was largely explained by the social contact features (total contact rate and assortativity) of children under 5. (5/6)
Happy to share our latest paper 📢 “Natural immune boosting biases pertussis infection estimates in seroprevalence studies.” https://t.co/K7QSqcDEuE
Read the🧵 to find out more! (1/6)
💡What is the implication? True infection burden is probably somewhere between reported case number and seropositivity-based estimates. Mathematical models integrating both data streams may get us a better estimate in the future! (5/6)
How does weather affect the transmission of infectious diseases, and how can we predict the effects of #climatechange on them? In our latest article published in @NatureEcoEvo, we explore these questions using #causalinference and #transmissionmodels. https://t.co/n9nFSwErwf
Integrating causal inference concepts with transmission models is necessary for inferring the effect of weather on infectious diseases and subsequently predicting the consequences of #climatechange on infectious diseases.