Description: Research project that assesses the accuracy of commonly used IBNR estimation methods for medical insurance over a wide range of scenarios. The methods are summarized, practical considerations in making the comparisons and the development of the data simulations for the comparisons are discussed.

Description: This report provides highlights of a weekly survey of practices regarding the mitigation of the spread of COVID-19 in the U.S. during the first half of March 2021 along with comparisons to prior half-month time periods. The survey asks about the degree to which the respondents perceive that people in their community are following 21 common mitigation practices. The responses are separated by state and compared to state level statistics regarding the level of COVID-19 infections from the Johns Hopkins COVID database for the same time period.

Description: The Patient Protection and Affordable Care Act (ACA) was signed into law March 23, 2010. The transformative health care legislation was multi-faceted, but its primary purpose was to reduce the number of uninsured Americans. In alignment with the SOA’s Strategic Plan objective to “inform the public’s understanding of key societal issues”, this report examines the various publications reporting on the uninsured rate which stakeholders frequently access to measure policy efficacy and inform future policy considerations.

Description: This report explores AI bias in insurance and health data, highlighting the ethical role of actuaries and offering cross-disciplinary guidance for fairer decision-making systems.

Description: This paper is about an Interacting Particle System [IPS] approach to modeling treatment costs associated with a multiple stage pandemic. The model population receives differing treatments with possibly differing costs depending on the stage of exposure/infection. The total cost of treatment is a time varying utility function of the ensemble population for which this approach uses particle system methods to simulate the cost of maintaining survival of the population. The paper gives a brief background on particle systems with specific focus on 'the contact process', followed by expanding the contact process to represent more realistic state transitions.

Description: Healthcare costs have been rising faster than general inflation for many years. Early models that predicted this past pattern projected healthcare expenditure growth that continued to outpace total expenditure growth leading to the fallacious position that the whole of the US economy would ultimately be consumed by healthcare. The Society of Actuaries' Pension Section and Health Section Research teams commissioned Professor Thomas E. Getzen of Temple University to construct a resource model for the projection of long term healthcare cost trends that includes capacity constraints to ensure the long-term projection is rational. The motivation for creation of the model was driven by its potential usage as a resource for the estimation of reportable liabilities for retiree healthcare benefits as specified under FAS 106 and GASB 45 accounting statements. This is a zip file containing the following: 1. A background paper on the creation of the health trend model, 2. The model, programmed in Microsoft Excel [xls format], that projects per-person expenditures and growth rates through 2099 using baseline assumptions, but also permits the flexibility for user–inputted alternative assumptions, and 3. Technical documentation providing transparency and support for the ultimate results.

Description: Loss ratio formulas that make it a good tool for financial analysis, with modifications for level premium business such as disability income and long term care.

Description: Health care cost trends are a key ingredient that health care actuaries use in their practice. In collaboration with the Health Care Cost Institute (HCCI), the Society of Actuaries has put together a data extract for practicing health actuaries to be able to better understand historical trends and cost disruptors.

Description: Since the outbreak began in January, numerous research groups throughout the world have developed models to forecast the number of deaths that could result from COVID-19. Updated April 24, 2020.

Description: This tool created graphs of Google's mobility Data. This version of the tool contains global, country-level data through July 31, 2020