Overview

Time series forecasting has emerged as a crucial analytical approach in epidemiology due to its potential to predict future disease patterns, identify emerging trends, and inform public health planning. Epidemiologists and health officials use time series data to track and analyze the occurrence of infectious diseases, chronic illnesses, and other health-related events over time. This rationale aims to elucidate the significance of time series forecasting in epidemiology, outlining its advantages, challenges, and real-world applications in combating disease outbreaks and shaping effective healthcare interventions. The relevance of Time Series Forecasting in Epidemiology is multifaceted. Firstly, it enables an understanding of the dynamic nature of Infectious Diseases. The number of cases fluctuates over time, influenced by factors such as human behaviour, vaccination campaigns, climate, and pathogen evolution. Time series forecasting techniques enable researchers to understand these complex dynamics and predict future disease spread patterns accurately. Secondly, effective resource allocation is essential for managing epidemics and ensuring the optimal use of limited healthcare resources. Time series forecasting provides insights into disease trends, enabling health officials to allocate resources proactively and respond swiftly to potential outbreaks, minimizing their impact. Thirdly, Epidemiologists and policymakers utilize time series forecasting to devise targeted intervention and control strategies. By identifying high-risk periods, population segments, and geographic areas, public health measures such as vaccination campaigns, quarantine protocols, and public awareness campaigns can be effectively tailored.

The time series forecasting workshop is an introductory half day workshop planned as a pre-conference CME for the participants of IPHACON 2024. The workshop introduces the participants to the concept of time series, its features, characteristics and components. This is followed by introduction to time series analysis and commonly used ARIMA and ETS models.

Topics Covered

Introduction to Time Series Data.
Time Series Analysis and Visualization.
Forecasting with ARIMA models
Forecasting with ETS models
Advanced Concepts: An overview to hierarchical models, deep learning models (eg LSTM) and Large Language Models (LLMs)

Resource Faculty

The resource faculty for the workshop are experienced professionals with expertise in spatial, time-series and spatiotemporal epidemiology, disease modelling, data science, health research, and public health practice.

Dr. Arun Kumar Yadav

Professor and Commanding Officer,
Armed Forces Medical Services,
India

Brief Bio

Dr. Arun Kumar Yadav ex Professor of Dept of Community Medicine, AFMC, Pune has guided four MD students and advised more than 1000 postgraduate/undergraduate researchers as secretary of the scientific committee and member secretary of ethics committee. He established a Multi-disciplinary unit (DHR-ICMR), GIS lab, and Health and demographic surveillance system in AFMC, Pune. He provided technical guidance for establishment of wellness center in AFMC, Pune. He is a recipient of three fellowship ( IPHA, IAPSM, AIPI) and members of 11 National and international organization. Currently he is holding the post of Joint secretary (West) in Indian public health association and academic editor of PLOS global health, earlier he was governing council member in IAPSM and executive editor of Indian Journal of Community Medicine. He has published more than 200 peer reviewed research articles in national and international journals (https://www.researchgate.net/profile/Arun-Yadav-12) and is reviewer for Nature medicine, PLOS one, MRC UK, IJPH and other reputed journals. He was assistant editor of WHO textbook of Community Medicine and public health. He is a member of national advisory board for prevention of COVID-19, implementation research and Health system reviews. He was part of team which piloted WHO tool for benchmarking Ethics oversight of Health-related research with human participants in India. He was a member of 15th common review mission for undertaking rapid assessment of functional status of national program under National health mission. He has also been regularly taking interactive session on epidemiology for National board of Examination and has conducted national workshops on systematic reviews, regression, STATA and ‘R’. Currently, he is posted in High altitude area, where he is leading projects for prevention of High-altitude illnesses. He has a special interest in evidence generation including Systematic review and meta-analysis, Hierarchical Modelling, stroke epidemiology, Health technology assessment, implementation research and ethics.

Dr. Gurpreet Singh

Associate Professor & Senior Medical Officer,
Armed Forces Medical Services,
India

Brief Bio

Dr. Gurpreet Singh is a physician, Epidemiologist, and Senior Medical Officer. He holds PhD in Health Data Science from Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum . Dr Gurpreet completed his MBBS and MD (Community Medicine) from Armed Forces Medical College, Pune in 2007 and 2015 respectively, DNB (Preventive and Social Medicine) from National Board of Examinations, India in 2016. He is recipient of Director General Armed Forces Medical Services Gold Medal, President’s NBE Gold Medal, Certificate of Merit from Maharashtra University of Health Sciences, General Officer Commanding Medallion, Best PhD paper award (IPHACON 2022), and Gavin Mooney Prize (IHEPA). He has contributed chapters to a few books and has 79 scientific publications. His PhD was focused on ”Data Science approach for Spatio-temporal modelling of Dengue in Punjab, India”. He has been an active member of National and International Associations and have contributed immensely towards evacuation of students from Ukraine, relief missions in Syria, and HADR operations during Turkiye earthquake. His area of interest includes Data Science, Epidemiology, Infectious Diseases, Outbreak control and Immunization among others. He is also a firm believer of reproducible science and has conducted multiple cohorts of workshops on introduction to R and R for Spatial Epidemiology.

Contact

In case of queries please contact:

+91 986 881 5430 - Dr. Arun K Yadav

+91 855 205 5667 - Dr. Gurpreet Singh

Please reach out for additional queries: drgurpreet.md.afmc@gmail.com

This work is licensed under a Creative Commons Attribution 4.0 International License.