Christopher L Gys, Stephanie L Haft, Qing Zhou
Relations between self-regulation and behavioral adjustment in Chinese American immigrant children during early elementary school years
Child development
covid19 pandemic plethora dynamical forecasting models created ability effectively describe future trajectories disease mixed major challenge evaluating future case trends forecasting behavior individuals behavior incorporated models primarily incorporated exogenously eg fitting cellphone mobility data fewer models incorporated behavior endogenously eg dynamically changing model parameter throughout simulation review aimed qualitatively characterize models included adaptive endogenous behavioral element context covid19 transmission categorized studies three approaches 1 feedback loops 2 game theoryutility theory 3 informationopinion spread 92 included studies 72 employed feedback loop 27 used gameutility theory 9 used model informationopinion spread among studies 89 used compartmental model alone combination model types similarly 15 used network model 11 used agentbased model 7 used system dynamics model 1 used markov chain model descriptors behavior change included maskwearing social distancing vaccination others sixtyeight percent studies calibrated model observed data 25 compared simulated forecasts observed data fortyone percent studies compared versions model without endogenous behavior models endogenous behavior tended show smaller delayed initial peak subsequent periodic waves many covid19 models incorporated behavior exogenously approaches may fail capture future adaptations human behavior resulting overestimates disease burden incorporating behavior endogenously next generation infectious disease models could effectively predict outcomes decision makers better prepare respond epidemics study funded inpart centers disease control prevention cdc mindhealthcare program 1u01ck000536 national science foundation nsf modeling dynamic diseasebehavior feedbacks improved epidemic prediction response grant 2229996 nsf pipp phase evaluating effectiveness messaging modeling pandemics grant 2200256