Spatial scales of COVID-19 transmission in Mexico (preprint)

During outbreaks of emerging infectious diseases, internationally connected cities often experience large and early outbreaks, while rural regions follow after some delay. This hierarchical structure of disease spread is influenced primarily by the multiscale structure of human mobility. However, during the COVID-19 epidemic, public health responses typically did not take into consideration the explicit spatial structure of human mobility when designing non-pharmaceutical interventions (NPIs). NPIs were applied primarily at national or regional scales. Here we use weekly anonymized and aggregated human mobility data and spatially highly resolved data on COVID-19 cases, deaths and hospitalizations at the municipality level in Mexico to investigate how behavioural changes in response to the pandemic have altered the spatial scales of transmission and interventions during its first wave (March - June 2020). We find that the epidemic dynamics in Mexico were initially driven by SARS-CoV-2 exports from Mexico State and Mexico City, where early outbreaks occurred. The mobility network shifted after the implementation of interventions in late March 2020, and the mobility network communities became more disjointed while epidemics in these communities became increasingly synchronised. Our results provide actionable and dynamic insights into how to use network science and epidemiological modelling to inform the spatial scale at which interventions are most impactful in mitigating the spread of COVID-19 and infectious diseases in general.

Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data (preprint)

Background. During 2021, the COVID-19 pandemic was characterized by the emergence of lineages with increased fitness. For most of these variants, quantitative information is scarce on epidemiological quantities such as the incubation period and generation time, which are critical for both public health decisions and scientific research. Method. We analyzed a dataset collected during contact tracing activities in the province of Reggio Emilia, Italy, throughout 2021. We determined the distributions of the incubation period using information on negative PCR tests and the date of last exposure from 282 symptomatic cases. We estimated the distributions of the intrinsic generation time (the time between the infection dates of an infector and its secondary cases under a fully susceptible population) using a Bayesian inference approach applied to 4,435 SARS-CoV-2 cases clustered in 1,430 households where at least one secondary case was recorded. Results. We estimated a mean incubation period of 4.9 days (95% credible intervals, CrI, 4.4-5.4; 95 percentile of the mean distribution: 1-12) for Alpha and 4.5 days (95%CrI 4.0-5.0; 95 percentile: 1-10) for Delta. The intrinsic generation time was estimated to have a mean of 6.0 days (95% CrI 5.6-6.4; 95 percentile: 1-15) for Alpha and of 6.6 days (95%CrI 6.0-7.3; 95 percentile: 1-18) for Delta. The household serial interval was 2.6 days (95%CrI 2.4-2.7) for Alpha and 2.4 days (95%CrI 2.2-2.6) for Delta, and the estimated proportion of pre-symptomatic transmission was 54-55% for both variants. Conclusions. These results indicate limited differences in the incubation period and intrinsic generation time of SARS-CoV-2 variants Alpha and Delta compared to ancestral lineages.

Designing isolation guidelines for COVID-19 patients utilizing rapid antigen tests: a simulation study using viral dynamics models (preprint)

Appropriate isolation guidelines for COVID-19 patients are warranted. Currently, isolating for fixed time is adapted in most countries. However, given the variability in viral dynamics between patients, some patients may no longer be infectious by the end of isolation (thus they are redundantly isolated), whereas others may still be infectious. Utilizing viral test results to determine ending isolation would minimize both the risk of ending isolation of infectious patients and the burden due to redundant isolation of noninfectious patients. In our previous study, we proposed a computational framework using SARS-CoV-2 viral dynamics models to compute the risk and the burden of different isolation guidelines with PCR tests. In this study, we extend the computational framework to design isolation guidelines for COVID-19 patients utilizing rapid antigen tests. Time interval of tests and number of consecutive negative tests to minimize the risk and the burden of isolation were explored. Furthermore, the approach was extended for asymptomatic cases. We found the guideline should be designed considering various factors: the infectiousness threshold values, the detection limit of antigen tests, symptom presence, and an acceptable level of releasing infectious patients. Especially, when detection limit is higher than the infectiousness threshold values, more consecutive negative results are needed to ascertain loss of infectiousness. To control the risk of releasing of infectious individuals under certain levels, rapid antigen tests should be designed to have lower detection limits than infectiousness threshold values to minimize the length of prolonged isolation, and the length of prolonged isolation increases when the detection limit is higher than the infectiousness threshold values, even though the guidelines are optimized for given conditions.

Model-based evaluation of alternative reactive class closure strategies against COVID-19 (preprint)

There are contrasting results concerning the effect of reactive school closure on SARS-CoV-2 transmission. To shed light on this controversy, here we develop a data-driven computational model of SARS-CoV-2 transmission to investigate mechanistically the effect on COVID-19 outbreaks of school closure strategies based on syndromic surveillance and antigen screening of students. We found that by reactively closing classes based on syndromic surveillance, SARS-CoV-2 infections are reduced by no more than 13.1% (95%CI: 8.6%-20.2 %), due to the low probability of timely symptomatic case identification among the young population. We thus investigated an alternative triggering mechanism based on repeated screening of students using antigen tests. Should population-level social distancing measures unrelated to schools enable maintaining the reproduction number (R) at 1.3 or lower, an antigen-based screening strategy is estimated to fully prevent COVID-19 outbreaks in the general population. Depending on the contribution of schools to transmission, this strategy can either prevent COVID-19 outbreaks for R up to 1.9 or to at least greatly reduce outbreak size in very conservative scenarios about school contribution to transmission. Moving forward, the adoption of antigen-based screenings in schools could be instrumental to limit COVID-19 burden while vaccines continue to roll out through 2021, especially in light of possible continued emergence of SARS-CoV-2 variants.

Characterizing all-cause excess mortality patterns during COVID-19 pandemic in Mexico (preprint)

BackgroundThe low testing rates, compounded by reporting delays, hinders the estimation of the mortality burden associated with the COVID-19 pandemic based on surveillance data alone. A more reliable picture of the effect of COVID-19 pandemic on mortality can be derived by estimating excess deaths above an expected level of death. In this study we aim to estimate the absolute and relative mortality impact of COVID-19 pandemic in Mexico in 2020 by gender and two geographic regions: Mexico City and the rest of the country. MethodsWe obtained mortality time series due to all causes for Mexico, and by gender, and geographic region using epidemiological weeks from January to December 2020 and for preceding 5 years. We also compiled data on COVID-19 related morbidity and mortality to assess the timing and intensity of the pandemic in Mexico. We assembled weekly series of the number of tweets about death from Mexico to assess the correlation between peoples media interaction about death and the rise in pandemic deaths. We estimated all-cause excess mortality rates and mortality rate ratio increase over baseline by fitting Serfling regression models. ResultsThe COVID-19 pandemic excess mortality rates per 10,000 population in Mexico between March 1, 2020 and January 2, 2021 was estimated at 26.10. The observed total number of deaths due to COVID-19 was 128,886 which is 38.64% of the total estimated excess deaths. Males had about 2-fold higher excess mortality rate (33.99) compared to females (18.53). The excess mortality rate for Mexico City (63.54) was about 2.7-fold higher than the rest of the country (23.25). Similarly, the mortality rate ratio relative to baseline was highest for Mexico City (RR: 2.09). There was no significant correlation between weekly number of tweets on death and the weekly all-cause excess mortality rates ({rho}=0.309 (95% CI: 0.010, 0.558, p-value=0.043). ConclusionThe excess mortality rate of 26.10 per 10,000 population corresponds to a total of 333,538 excess deaths in Mexico between March 1, 2020 to January 2, 2021. COVID-19 accounted for only 38.21% of the total excess deaths, which reflects either the effect of low testing rates in Mexico, or the surge in number of deaths due to other causes.

Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March 20-November 11, 2020. (preprint)

Mexico has experienced one of the highest COVID-19 death rates in the world. A delayed response towards implementation of social distancing interventions until late March 2020 and a phased reopening of the country in June 2020 has facilitated sustained disease transmission in the region. Here, we systematically generate and compare 30-day ahead forecasts using previously validated growth models based on mortality trends from the Institute for Health Metrics and Evaluation for Mexico and Mexico City in near real-time. Moreover, we estimate reproduction numbers for SARS-CoV-2 based on methods that rely on genomic data as well as case incidence data. Subsequently, functional data analysis techniques are utilized to analyze the shapes of COVID-19 growth rate curves at the state level to characterize the spatial-temporal transmission patterns. The early estimates of reproduction number for Mexico were estimated between R[~]1.1-from genomic and case incidence data. Moreover, the mean estimate of R has fluctuated [~]1.0 from late July till end of September 2020. The spatial analysis characterizes the state-level dynamics of COVID-19 into four groups with distinct epidemic trajectories. We found that the sequential mortality forecasts from the GLM and Richards model predict downward trends in the number of deaths for all thirteen forecasts periods for Mexico and Mexico City. The sub-epidemic and IHME models predict more realistic stable trajectory of COVID-19 mortality trends for the last three forecast periods (09/21-10/21 - 09/28-10/27) for Mexico and Mexico City. Our findings support the view that phenomenological models are useful tools for short-term epidemic forecasting albeit forecasts need to be interpreted with caution given the dynamic implementation and lifting of social distancing measures.

HIV testing by public health centers and municipalities, and new HIV cases during the COVID-19 pandemic in Japan (preprint)

BackgroundDuring the COVID-19 outbreak, medical resources were primarily allocated to COVID-19, which might have reduced facility capacity for HIV testing. Further, people may have opted against HIV testing during this period to avoid COVID-19 exposure. We investigate the influence of the COVID-19 pandemic on HIV testing and its consequences in Japan. MethodsWe analysed quarterly HIV/AIDS-related data from 2015 to the second quarter of 2020 using an anomaly detection approach. The data included the number of consultations that public health centers received, the number of HIV tests performed by public health centers or municipalities, and the number of newly reported HIV cases with and without AIDS diagnosis. As sensitivity analyses, we performed the same analysis for two subgroups: men who have sex with men (MSM) and non-Japanese. FindingsThe number of HIV tests (9,584 vs. 35,908 in the year-before period) and consultations (11,689 vs. 32,565) performed by public health centers significantly declined in the second quarter of 2020, while the proportion of HIV cases with AIDS diagnosis among all HIV cases (36{middle dot}2% vs. 26{middle dot}4%) significantly increased after removing the trend and seasonality effects. The number of HIV cases without AIDS diagnosis numerically decreased (166 vs. 217), although the reduction was not significant. We confirmed similar trend for the MSM and non-Japanese groups. InterpretationThe current HIV testing system including public health centers misses more HIV cases at the early phase of the infection during the pandemic. Given that the clear epidemiological picture of HIV incidence during the pandemic is still uncertain, continuously monitoring the situation as well as securing sufficient test resources using self-test is essential. FundingJapan Society for the Promotion of Science, Japan Science and Technology Agency, Japan Agency for Medical Research and Development. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSBefore this study, we searched PubMed, Medline, and Google Scholar on Oct 12, 2020, for articles investigated the number of HIV test and HIV cases during the COVID-19 pandemic in Japan, using the search terms "novel coronavirus" or "SARS-CoV-2", and "HIV" or "AIDS", and "Japan", with no time restrictions. We found no published work relevant to our study. Added value of this studyDuring the COVID-19 pandemic in Japan, the public health centers and municipalities temporarily suspended facility-based HIV testing to concentrate their limited resources to COVID-19 testing. We investigated the impact of the COVID-19 pandemic on the number of HIV tests in public health centers and municipalities, and on the number of HIV cases with and without AIDS diagnosis. We confirmed that the number of the test declined in the second quarter (April to June) of 2020, and the proportion of HIV with AIDS diagnosis among all HIV cases increased during the same period. Implications of all the available evidenceProviding sufficient HIV testing opportunities even during the pandemic, when facility-based testing is challenging, is necessary for better clinical and public health outcomes. Self-testing and home specimen collection (e.g. dried blood spot or oral fluid test) could be a key to fill the gap between the need for HIV testing and the constraints related to the COVID-19 outbreak.

College Openings, Mobility, and the Incidence of COVID-19 Cases (preprint)

Most U.S. colleges have reopened campuses for in-person teaching this Fall, following rapid closures at the onset of the COVID-19 pandemic this Spring. Despite administrative efforts at mitigation and preventive measures, the large congregation of students within close quarters has caused public health concerns. In this paper, we examine college reopenings' association with changes in human mobility within campuses and in COVID-19 incidence in the counties of the campuses, over a two-week period before and after college reopenings. To estimate the daily reproduction number (Rt), we used a Bayesian framework. Using a difference-in-differences design comparing areas with a college campus, before and after reopening, to areas without a campus, we find that after college reopenings for face-to-face instruction, COVID-19 incidence in the county increased on average by a statistically significant 0.024 per thousand residents, following increases in mobility on campus. Similarly, we estimated increased transmission locally after reopening, with a rising trend in Rt. The increase in cases was larger in counties with colleges that drew students from areas with increasing incidence rates.

The COVID-19 outbreak in Sichuan, China: epidemiology and impact of interventions (preprint)

In January 2020, a COVID19 outbreak was detected in Sichuan Province of China. The aim of this work is to characterize the epidemiology of the Sichuan outbreak and estimate the impact of the performed interventions. We analyzed patient records for all laboratory confirmed cases reported in the province for the period of January 21 to March 16, 2020. To estimate the basic and daily reproduction numbers, we used a Bayesian framework. In addition, we estimate the number of cases averted by the implemented control strategies. The outbreak resulted in 539 confirmed cases, lasted less than two months, and no further local transmission was detected after February 27. The median age of local cases was 8 years older than that of imported cases. Severity of symptoms increased with age. We estimated R0 at 2.4 (95% CI: 1.6-3.7). The epidemic was self sustained for about 3 weeks before going below the epidemic threshold 3 days after the declaration of a public health emergency by Sichuan authorities. Our findings indicate that, were the control measures be adopted four weeks later, the epidemic could have lasted 49 days longer (95%CI: 31-68 days), causing 9,216 (95%CI: 1,317-25,545) more cases and possibly overwhelming Sichuan healthcare system.

Estimation of the incubation period of COVID-19 using viral load data (preprint)

The incubation period, or the time from infection to symptom onset of COVID-19 has been usually estimated using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in recalling effort of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used the reported viral load data from multiple countries (Singapore, China, Germany, France, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.23 days (95% CI: 5.17, 5.25), 3.29 days (3.25, 3.37), and 8.22 days (8.02, 8.46), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach especially when impractical to directly observe the infection event.

Information Seeking Responses to News of Local COVID-19 Cases: Evidence from Internet Search Data (preprint)

The novel coronavirus (COVID-19) outbreak is a global pandemic with community circulation in many countries, including the U.S. where every state is reporting confirmed cases. The course of this pandemic will be largely shaped by how governments enact timely policies, disseminate the information, and most importantly, how the public reacts to them. Here, we examine informationseeking responses to the first COVID-19 case public announcement in a state. By using an eventstudy framework, we show that such news increases collective attention to the crisis right away, but the elevated level of attention is short-lived, even though the initial announcements were followed by increasingly strong measures. We find that people respond to the first report of COVID-19 in their state by immediately seeking information about COVID-19, as measured by searches for coronavirus, coronavirus symptoms and hand sanitizer. On the other hand, searches for information regarding community level policies (e.g., quarantine, school closures, testing), or personal health strategies (e.g., masks, grocery delivery, over-the-counter medications) do not appear to be immediately triggered by first reports. These results are encouraging given our study period is relatively early in the epidemic and more elaborate policy responses were not yet part of the public discourse. Further analysis will track evolving patterns of responses to subsequent flows of public information.

Inferring Timing of Infection Using Within-host SARS-CoV-2 Infection Dynamics Model: Are "Imported Cases" Truly Imported? (preprint)

Importance: Although the COVID-19 epidemic in some countries such as China are in the last phase by large effort for containment of the disease, another outbreaks can occur because huge susceptible population remains. Further, there remain countries in the early phase of outbreak with zero or limited number of cases in southern hemisphere countries. In those countries at risk of future outbreak, ascertaining whether cases are imported or the result of local secondary transmission is important for government to shape appropriate public health strategies. Objective: To develop a method to estimate timing of infection establishment, which helps differentiate imported and autochthonous cases. Design, Setting and Participants: Of the first 18 cases reported in Singapore, 12 were used in our study (1 case with insufficient data and 5 on anti-viral treatment were excluded from the analysis). The viral load data from these initial cases considered imported due to their travel history to Wuhan were analyzed. Another viral load data from 3 cases reported from Zhuhai, China, for whom exposed day were known, were also analyzed to determine the viral load threshold for infection establishment. Exposures: SARS-CoV-2 infection confirmed by the polymerase-chain-reaction (PCR) test. Main Outcomes and Measures: The timing of infection establishment of each case was assessed by analysing viral load data after symptom onset using a within-host viral dynamics model for SARS-CoV-2. Estimated timing of infection will indicate whether cases are imported or autochthonous transmission within Singapore. Results: Six among the 12 cases were clearly imported cases, whereas we could not rule out the possibility of secondary transmission for the rest of 6 cases, which collectively evidenced ongoing transmission in Singapore. For the 6 cases who could be the results of secondary transmission, further investigation to identify the source of infection within Singapore should be warranted (i.e., contact tracing). Conclusions and Relevance: In an early phase of outbreak due to entrance or re-entrance of the virus to countries/communities, collecting viral load data over time from cases from symptom onset is highly recommended, because viral load data are valuable to infer the timing of infection and distinguish between imported cases and ongoing local transmission.