No abstract

The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned. By making any designation of or reference to a particular territory or geographic area, or by using the term "country" in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.

Accurate mortality data are critical for understanding the impact of COVID-19 and learning lessons from crisis responses. But official statistics risk undercounting deaths due to limited testing and underreporting, especially in developing countries. Thailand has experienced four COVID-19 waves and used a color-coded, province-level system for lockdowns. To account for deaths directly and indirectly caused by COVID-19, this paper uses mixed-effects modelling to estimate counterfactual deaths from January 2020 to December 2021 and construct a monthly time series of provincial excess mortality. The model reveals that excess mortality was much higher than official figures, with the largest undercounting for males and the elderly. Then, recently developed panel regression methods are used to characterize the correlations among restrictions, mobility, and excess mortality. The findings suggest that lockdowns stemmed excess mortality with a three-month lag.

In partnership with the Food and Agriculture Organization of the United Nations, the Asian Development Bank developed two freely accessible massive open online courses (MOOCs) to provide statistical capacity building in computer-assisted personal interviewing (CAPI) globally. CAPI typically takes the form of tabletbased survey data collection. One of the courses focused on the CSPro platform; the other on Survey Solutions.• The two courses, which comprised eight modules of videos, exercises, and quizzes, ran concurrently over 8 weeks in early 2019.• The 655 students who enrolled from around the world could choose to take one CAPI course or both together.• The CSPro course had a completion rate of 35%, and the Survey Solutions course of 37%-well above the typical MOOC completion rates of between 2% and 14%.• The per-student cost for the MOOCs is estimated to be 7 times lower than equivalent classroom training conducted by ADB, as MOOCs significantly reduce logistical, transportation, and personnel costs. Further, the potential to conduct additional rounds of the MOOCs with minimal maintenance costs means that the per capita costs will reduce over time.• A second round of the two CAPI courses will be launched in mid-June 2020. Interested learners can register at: https://forms.gle/ bE7LdqzneuvsTko88.

The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned. By making any designation of or reference to a particular territory or geographic area, or by using the term "country" in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.