Swapnil Mishra
Latest
- Robert Verity, Samir Bhatt, Anne Cori, Seth Flaxman, and Swapnil Mishra’s contribution to the Discussion of ‘Some statistical aspects of the Covid-19 response’ by Wood et al.
- Estimating the worst-case scenario for malaria parasite rate in sub-Saharan Africa
- Exploring the potential and limitations of deep learning and explainable AI for longitudinal life course analysis
- Ethnicity and anthropometric deficits in children: A cross-sectional analysis of national survey data from 18 countries in sub-Saharan Africa
- Modelling the impact of vaccination on SARS-CoV-2 transmission in England
- The interaction of disease transmission, mortality, and economic output over the first 2 years of the COVID-19 pandemic
- Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya
- Application of referenced thermodynamic integration to Bayesian model selection
- Machine learning models of healthcare expenditures predicting mortality: A cohort study of spousal bereaved Danish individuals
- Predicting mortality risk after a fall in older adults using health care spending patterns: a population-based cohort study
- Unifying incidence and prevalence under a time-varying general branching process
- Intrinsic Randomness in Epidemic Modelling Beyond Statistical Uncertainty
- A comparison of short-term probabilistic forecasts for the incidence of COVID-19 using mechanistic and statistical time series models
- Effectiveness assessment of non-pharmaceutical interventions: lessons learned from the COVID-19 pandemic
- Sex differences in health care expenditures and mortality after spousal bereavement: A register-based Danish cohort study
- Semi-mechanistic Bayesian modelling of COVID-19 with renewal processes
- Assessment of COVID-19 as the Underlying Cause of Death Among Children and Young People Aged 0 to 19 Years in the US
- A COVID-19 Model for Local Authorities of the United Kingdom
- Authors’ Reply to the Discussion of ‘A COVID-19 Model for Local Authorities of the United Kingdom’ by Mishra et al. in Session 2 of the Royal Statistical Society’s Special Topic Meeting on COVID-19 Transmission: 11 June 2021
- Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes
- $$\pi $$VAE: a stochastic process prior for Bayesian deep learning with MCMC
- Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience
- PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation
- Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling
- Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals
- A dataset of non-pharmaceutical interventions on SARS-CoV-2 in Europe
- πVAE: a stochastic process prior for Bayesian deep learning with MCMC
- Epidemia: An R Package for Semi-Mechanistic Bayesian Modelling of Infectious Diseases using Point Processes
- PriorVAE: Encoding spatial priors with VAEs for small-area estimation
- Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe
- Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling
- Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England
- Is the cure really worse than the disease? The health impacts of lockdowns during COVID-19
- Maps and metrics of insecticide-treated net access, use, and nets-per-capita in Africa from 2000-2020
- Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria
- Modelling the impact of the tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns
- Using Hawkes Processes to model imported and local malaria cases in near-elimination settings
- Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England
- Age groups that sustain resurging COVID-19 epidemics in the United States
- A unified machine learning approach to time series forecasting applied to demand at emergency departments
- Referenced Thermodynamic Integration for Bayesian Model Selection: Application to COVID-19 Model Selection