On the role of statisticians and modelers in responding to AIDS and COVID-19

The Impact of COVID-19 on Disruptions of HIV-related Services: A Rapid Review

Background: People living with HIV (PLHIV) and those at risk of HIV are marginalized worldwide and need to reach services regularly. The COVID-19 pandemic can disrupt the HIV care continuum. This study aimed to identify the extent to which HIV-related services have been affected by the COVID-19 pandemic and how we can overcome these challenges. Methods: In this rapid review, we systematically searched PubMed and Scopus databases, the references of studies, international agencies, and studies "cited by" feature in google scholar till May 28, 2021, without restrictions to language. Results: Among the total of 1,121 studies, 31 of them were included in the review. The most important HIV-related services affected by the COVID-19 pandemic were; access to anti-retroviral drugs, HIV testing, periodic HIV-related testing in people living with HIV (PLHIV), pre-exposure prophylaxis, post-exposure prophylaxis, harm reduction services, psychological and counseling services. Some factors were introduced to mitigate the effects of these challenges, including increasing the resilience of health, protecting health care workers and their clients against COVID-19 through vaccination, providing HIV-related services through telehealth, and multi-month dispensing (MMD) of medicines. Conclusion: The results of this review study showed that PLHIV had difficulty in accessing follow-up, care and treatment services during the COVID-19 pandemic. Programs such as the MMD or telemedicine can be useful in providing services to PLHIV during the pandemic.

On the use of the reproduction number for SARS-CoV-2: Estimation, misinterpretations and relationships with other ecological measures

The basic reproduction number, R 0, and its real-time analogue, Rt , are summary measures that reflect the ability of an infectious disease to spread through a population. Estimation methods for Rt  have a long history, have been widely developed and are now enhanced by application to the COVID-19 pandemic. While retrospective analyses of Rt have provided insight into epidemic dynamics and the effects of control strategies in prior outbreaks, misconceptions around the interpretation of Rt have arisen with broader recognition and near real-time monitoring of this parameter alongside reported case data during the COVID-19 pandemic. Here, we discuss some widespread misunderstandings regarding the use of Rt  as a barometer for population risk and its related use as an 'on/off' switch for policy decisions regarding relaxation of non-pharmaceutical interventions. Computation of Rt  from downstream data (e.g. hospitalizations) when infection counts are unreliable exacerbates lags between when transmission happens and when events are recorded. We also discuss analyses that have shown various relationships between Rt  and measures of mobility, vaccination coverage and a test-trace-isolation intervention in different settings.

The role of statisticians in the response to COVID-19 in Israel: a holistic point of view

The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis to project them into the future. Statisticians in Israel were involved in these processes early in the pandemic in some silos as an ad-hoc unorganized effort. Informal discussions within the statistical community culminated in a roundtable, organized by three past presidents of the Israel Statistical Association, and hosted by the Samuel Neaman Institute in April 2021. The meeting was designed to provide a forum for exchange of views on the profession's role during the COVID-19 pandemic, and more generally, on its influence in promoting evidence-based public policy. This paper builds on the insights and discussions that emerged during the roundtable meeting and presents a general framework, with recommendations, for involving statisticians and statistics in decision-making.