Welcome to the first of two volumes of the ACM Transactions on Spatial Algorithms and Systems’s special issue on “Understanding the Spread of COVID-19.” Infectious disease spread within the human population can be conceptualized as a complex system composed of individuals that interact and transmit viruses via spatiotemporal processes that manifest across and between scales [
6,
9,
15]. The manifestation of individuals’ behavior in the space-time continuum is essential to the understanding, prediction, and efficient response when it comes to disease outbreaks [
19,
20]. Despite its crucial importance in pandemic prevention and response, our understanding of how spatiotemporal behavior affects the spread of infectious diseases is limited [
7].
To improve this understanding, newsletters, and workshops have been organized to bring together experts in spatiotemporal data, public health, epidemiology, and social sciences. Specifically, immediately upon the onset of the COVID-19 pandemic, in March 2020, the ACM SIGSPATIAL Newsletter released a call for papers for COVID-19 related articles that led to two special issues on “Understanding the Spread of COVID-19” [
30,
31], published rapidly in July 2020 and November 2020. Newsletter articles included work on COVID-19 data sources [
24], mapping mobility changes during COVID-19 [
13], COVID-19 cluster detection [
14,
17], epidemic simulation [
12], contact tracing [
21,
29], and spread forecasting [
8,
18]. To discuss results, the “1st ACM SIGSPATIAL International Workshop on Modeling and Understanding the Spread of COVID-19” [
5] has been co-located with ACM SIGSPATIAL’20 and the “2nd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology” [
4] has been co-located with ACM SIGSPATIAL’21. These interdisciplinary workshops featured keynotes by experts in epidemiology, public health, and biostatistics and presented 11 more papers on related topics, including infection risk estimation [
2,
16], disease monitoring [
1], epidemic simulation [
23,
26,
27], impact of COVID-19 on education [
28], COVID-19 cluster detection [
3], spatiotemporal analysis [
10,
11], and spatiotemporal visualization [
25]. Finally, in January 2022, Dagstuhl Seminar 22021 on Mobility Data Science [
22] discussed the role of human mobility in the understanding of disease ecology among many other topics.
This plethora of research shows how many research were working on understanding the spread of COVID-19 in their respective communities. To provide a forum to publish research results that may be inspired from the discussions had in aforementioned newsletter articles and workshops, this special issue was announced in January 2021 with a submission deadline on May 31, 2021. We received 28 submissions, of which 13 manuscripts have been accepted for publication. The topics range from examining the impacts of city lockdown on human mobility and the association with COVID-19 spread to infection diagnosis using X-ray images. Of the 13 accepted manuscripts, 5 manuscripts were accepted after one round of revision and 8 manuscripts were accepted after two rounds of revision. Of the 15 rejected manuscripts 11 were rejected in the first round and 4 were rejected after a revision. We want to cordially thank the many reviewers around the world for their diligent work that has helped the authors to substantially improve their manuscripts.