Kavi Bhalla

Associate Professor
Research Summary
Kavi Bhalla, PhD, is an Associate Professor in the Department of Public Health Sciences of the Biological Sciences Division at the University of Chicago, and Affiliated Faculty at the Harris School of Public Policy. His research aims to develop transport systems that are safe, sustainable and equitable, with a central focus on road safety in low- and middle-income countries. His recent work has focused on the development of analytical tools for improving estimates of the incidence of injuries in information-poor settings using available data sources. Kavi co-led the injury expert group of the 2010 Global Burden of Disease Project. He is formally trained as a mechanical engineer and his PhD (Cornell, 2001) thesis research focused on the mechanics of material failure, which he later applied to the study of injury biomechanics and vehicle crashworthiness. He is broadly interested in the design of products, environments, and systems that are safe and have positive health impacts.
Keywords
Global Health, Injury prevention, Traffic Accident, Road safety, Burden of disease
Education
  • Harvard University, Initiative for Global Health, Cambridge, MA, Ellison Fellow Population health metrics 2007
  • Harvard University, Center for Population and Development Studies, Cambridge, MA, Bell Fellow Public health policy 2005
  • Cornell University, Ithaca, NY, PhD Theoretical and Applied Mechanics 08/2001
  • Indian Institute of Technology - Delhi, New Delhi, India, BTech Mechanical Engineering 07/1995
Biosciences Graduate Program Association
Publications
  1. Estimated potential death and disability averted with vehicle safety interventions, Association of Southeast Asian Nations. Bull World Health Organ. 2023 Mar 01; 101(3):211-222. View in: PubMed

  2. Addressing discrepancies in estimates of road traffic deaths and injuries in Ethiopia. Inj Prev. 2022 Dec 05. View in: PubMed

  3. The effectiveness of fixed speed cameras on Iranian taxi drivers: An evaluation of the influential factors. Front Public Health. 2022; 10:964214. View in: PubMed

  4. The effect of non-punitive peer comparison and performance feedback on drivers' behavior using the telematics: The first randomized trial in Iran. J Safety Res. 2022 09; 82:430-437. View in: PubMed

  5. Estimates of road traffic deaths in Tanzania. Inj Prev. 2022 10; 28(5):422-428. View in: PubMed

  6. A systematic review and meta-analysis of the impact of curbs on crash outcomes. Traffic Inj Prev. 2022; 23(5):271-276. View in: PubMed

  7. Comparing estimates of road traffic deaths and non-fatal road traffic injuries in Cambodia. Inj Prev. 2022 08; 28(4):340-346. View in: PubMed

  8. Correction: An Approach Towards Reducing Road Traffic Injuries and Improving Public Health Through Big Data Telematics: A Randomised Controlled Trial Protocol. Arch Iran Med. 2022 01 01; 25(1):76. View in: PubMed

  9. Availability of population-level data sources for tracking the incidence of deaths and injuries from road traffic crashes in low-income and middle-income countries. BMJ Glob Health. 2021 11; 6(11). View in: PubMed

  10. Protecting the vulnerable by design - a tribute to Dinesh Mohan(1945-2021). Int J Inj Contr Saf Promot. 2021 09; 28(3):277-289. View in: PubMed

  11. Strengthening the Capacity of Emergency Medical Services in Low and Middle Income Countries using Dispatcher-Coordinated Taxis. Transp Res Rec. 2020 Sep 01; 2674(9):338-345. View in: PubMed

  12. Effects of vehicle safety design on road traffic deaths, injuries, and public health burden in the Latin American region: a modelling study. Lancet Glob Health. 2020 06; 8(6):e819-e828. View in: PubMed

  13. Fire-related deaths among women in India are underestimated. Lancet. 2020 03 07; 395(10226):779-780. View in: PubMed

  14. Monitoring India's progress on road safety will require investment in data systems. Lancet Public Health. 2020 02; 5(2):e82. View in: PubMed

  15. How much would low- and middle-income countries benefit from addressing the key risk factors of road traffic injuries? Int J Inj Contr Saf Promot. 2020 Mar; 27(1):83-90. View in: PubMed

  16. What can we learn from the historic road safety performance of high-income countries? Int J Inj Contr Saf Promot. 2020 Mar; 27(1):27-34. View in: PubMed

  17. The care and transport of trauma victims by layperson emergency medical systems: a qualitative study in Delhi, India. BMJ Glob Health. 2019; 4(6):e001963. View in: PubMed

  18. Going to the nearest hospital vs. designated trauma centre for road traffic crashes: estimating the time difference in Delhi, India. Int J Inj Contr Saf Promot. 2019 Sep; 26(3):271-282. View in: PubMed

  19. Building Road Safety Institutions in Low- and Middle-Income Countries: The Case of Argentina. Health Syst Reform. 2019; 5(2):121-133. View in: PubMed

  20. Using street imagery and crowdsourcing internet marketplaces to measure motorcycle helmet use in Bangkok, Thailand. Inj Prev. 2020 04; 26(2):103-108. View in: PubMed

  21. An Approach Towards Reducing Road Traffic Injuries and Improving Public Health Through Big Data Telematics: A Randomised Controlled Trial Protocol. Arch Iran Med. 2018 11 01; 21(11):495-501. View in: PubMed

  22. Estimating city-level travel patterns using street imagery: A case study of using Google Street View in Britain. PLoS One. 2018; 13(5):e0196521. View in: PubMed

  23. Impact of improving vehicle front design on the burden of pedestrian injuries in Germany, the United States, and India. Traffic Inj Prev. 2017 11 17; 18(8):832-838. View in: PubMed

  24. Estimating the burden of injury in urban and rural Sudan in 2008. Inj Prev. 2017 06; 23(3):171-178. View in: PubMed

  25. Official government statistics of road traffic deaths in India under-represent pedestrians and motorised two wheeler riders. Inj Prev. 2017 02; 23(1):1-7. View in: PubMed

  26. Burden Calculator: a simple and open analytical tool for estimating the population burden of injuries. Inj Prev. 2016 Apr; 22 Suppl 1:i23-6. View in: PubMed

  27. Long-term outcomes of individuals injured in motor vehicle crashes: A population-based study. Injury. 2015 Aug; 46(8):1503-8. View in: PubMed

  28. Automated speed enforcement systems to reduce traffic-related injuries: closing the policy implementation gap. Inj Prev. 2016 Feb; 22(1):79-83. View in: PubMed

  29. Evidence to inform intersectoral policies: a comparison of health and transport sector evidence in support of road traffic injury prevention. Health Res Policy Syst. 2015 Mar 25; 13:19. View in: PubMed

  30. GBD-2010 overestimates deaths from road injuries in OECD countries: new methods perform poorly. Int J Epidemiol. 2015 Oct; 44(5):1648-56. View in: PubMed

  31. Rapid assessment of road safety policy change: relaxation of the national speed enforcement law in Russia leads to large increases in the prevalence of speeding. Inj Prev. 2015 Feb; 21(1):53-6. View in: PubMed

  32. Seatbelt wearing rates in middle income countries: a cross-country analysis. Accid Anal Prev. 2014 Oct; 71:115-9. View in: PubMed

  33. Respondents' recall of injury events: an investigation of recall bias in cross-sectional injury data from the Sudan Household Health Survey 2010. Int J Inj Contr Saf Promot. 2015; 22(3):215-23. View in: PubMed

  34. The prevalence of speeding and drunk driving in two cities in China: a mid project evaluation of ongoing road safety interventions. Injury. 2013 Dec; 44 Suppl 4:S49-56. View in: PubMed

  35. The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA. 2013 Aug 14; 310(6):591-608. View in: PubMed

  36. The health effects of motorization. PLoS Med. 2013; 10(6):e1001458. View in: PubMed

  37. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012 Dec 15; 380(9859):2197-223. View in: PubMed

  38. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012 Dec 15; 380(9859):2163-96. View in: PubMed

  39. Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010. Lancet. 2012 Dec 15; 380(9859):2129-43. View in: PubMed

  40. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012 Dec 15; 380(9859):2095-128. View in: PubMed

  41. Non-traditional data sources for injury control: an agenda for action in Ghana. Inj Prev. 2012 Aug; 18(4):277. View in: PubMed

  42. Improving the quality of road injury statistics by using regression models to redistribute ill-defined events. Inj Prev. 2013 Feb; 19(1):1-5. View in: PubMed

  43. National burden of road traffic injuries in Argentina. Int J Inj Contr Saf Promot. 2012; 19(1):9-18. View in: PubMed

  44. The global injury mortality data collection of the Global Burden of Disease Injury Expert Group: a publicly accessible research tool. Int J Inj Contr Saf Promot. 2011 09; 18(3):249-53. View in: PubMed

  45. Availability and quality of cause-of-death data for estimating the global burden of injuries. Bull World Health Organ. 2010 Nov 01; 88(11):831-838C. View in: PubMed

  46. An urgent need to restrict access to pesticides based on human lethality. PLoS Med. 2010 Oct 26; 7(10):e1000358. View in: PubMed

  47. Estimating the incidence of road traffic fatalities and injuries in Sri Lanka using multiple data sources. Int J Inj Contr Saf Promot. 2010 Dec; 17(4):239-46. View in: PubMed

  48. Methods for developing country level estimates of the incidence of deaths and non-fatal injuries from road traffic crashes. Int J Inj Contr Saf Promot. 2009 Dec; 16(4):239-48. View in: PubMed

  49. Adverse health outcomes of road traffic injuries in Iran after rapid motorization. Arch Iran Med. 2009 May; 12(3):284-94. View in: PubMed

  50. Fire-related deaths in India in 2001: a retrospective analysis of data. Lancet. 2009 Apr 11; 373(9671):1282-8. View in: PubMed

  51. Data sources for improving estimates of the global burden of injuries: call for contributors. PLoS Med. 2009 Jan 20; 6(1):e1. View in: PubMed

  52. Estimating the distribution of external causes in hospital data from injury diagnosis. Accid Anal Prev. 2008 Nov; 40(6):1822-9. View in: PubMed

  53. Injury tolerance and moment response of the knee joint to combined valgus bending and shear loading. J Biomech Eng. 2008 Jun; 130(3):031008. View in: PubMed

  54. A risk-based method for modeling traffic fatalities. Risk Anal. 2007 Feb; 27(1):125-36. View in: PubMed

  55. Child and adult pedestrian impact: the influence of vehicle type on injury severity. Annu Proc Assoc Adv Automot Med. 2003; 47:105-26. View in: PubMed