To monitor the evolution of household living conditions during the COVID-19 pandemic, the World Bank con￾ducted COVID-19 High-Frequency Phone Surveys in around 80 countries. Phone surveys are cheap and easy to implement, but they have some major limitations, such as the absence of poverty data, sampling bias due to incomplete telephone coverage in many developing countries, and fre￾quent nonresponses to phone interviews. To overcome these limitations, the World Bank conducted pilots in 20 coun￾tries where the Survey of Wellbeing via Instant and Frequent Tracking, a rapid poverty monitoring tool, was adopted to estimate poverty rates based on 10 to 15 simple questions collected via phone interviews, and where sampling weights were adjusted to correct the sampling and nonresponse bias. This paper examines whether reweighting procedures and the Survey of Wellbeing via Instant and Frequent Tracking methodology can eliminate the bias in poverty estimation based on the COVID-19 High-Frequency Phone Surveys. Experiments using artificial phone survey samples show that (i) reweighting procedures cannot fully eliminate bias in poverty estimates, as previous research has demon￾strated, but (ii) when combined with Survey of Wellbeing via Instant and Frequent Tracking poverty projections, they effectively eliminate bias in poverty estimates and other statistics.