Evaluation of the exit screening policy among travelers arriving from Asian and pacific nations.

BACKGROUND: The Japanese government has instituted border control measures against COVID-19, including entry and exit screening of people arriving from overseas. We sought to evaluate the effectiveness of the exit screening policy in Japan in reducing the risk of importing COVID-19 cases among travelers from Asian and Pacific countries. METHODS: The study period was stratified based on the timing of exit screening: (i) the control period (the pre-exit screening period from 25 October 2020 to 16 January 2021), (ii) the time period with the Alpha variant from 17 January to 10 April 2021, and (iii) the time period with the Delta variant from 2 May to 2 October 2021. Incidence data in the countries of origin were used to adjust for the risk of infection among travelers. The positivity rate of entry screening in Japan was compared among the three different study periods, adjusting for the risk of infection in the country of origin. RESULTS: The adjusted relative risk of positivity was greatly reduced and substantially below the value of 1 during the Alpha variant period compared with the control period. Although the relative risks increased when comparing the Delta variant period against control, the estimate remained below 1, except for among travelers from India and Myanmar. The relative risk reduction was greatest in high-income countries, with estimates of 100% and 96% risk reduction during the Alpha and Delta variant periods, respectively, followed by upper-middle-income countries with estimates of 90% and 76%, respectively. CONCLUSIONS: Even in the presence of the Alpha and Delta variants, exit screening clearly reduced the risk of infection among travelers arriving from Asian and Pacific nations. As the testing relies on the country of origin, the effectiveness varied greatly by the socioeconomic income status and epidemiological situation of those countries. Test standardization and quality assurance may be required in low- and middle-income countries.

Reconstructing the COVID-19 incidence in India using airport screening data in Japan.

BACKGROUND: A major epidemic of COVID-19 caused by the Delta variant (B.1.617.2) occurred in India from March to July 2021, resulting in 19 million documented cases. Given the limited healthcare and testing capacities, the actual number of infections is likely to have been greater than reported, and several modelling studies and excess mortality research indicate that this epidemic involved substantial morbidity and mortality. METHODS: To estimate the incidence during this epidemic, we used border entry screening data in Japan to estimate the daily incidence and cumulative incidence of COVID-19 infection in India. Analysing the results of mandatory testing among non-Japanese passengers entering Japan from India, we calculated the prevalence and then backcalculated the incidence in India from February 28 to July 3, 2021. RESULTS: The estimated number of infections ranged from 448 to 576 million people, indicating that 31.8% (95% confidence interval (CI): 26.1, 37.7) - 40.9% (95% CI: 33.5, 48.4) of the population in India had experienced COVID-19 infection from February 28 to July 3, 2021. In addition to obtaining cumulative incidence that was consistent with published estimates, we showed that the actual incidence of COVID-19 infection during the 2021 epidemic in India was approximately 30 times greater than that based on documented cases, giving a crude infection fatality risk of 0.47%. Adjusting for test-negative certificate before departure, the quality control of which was partly questionable, the cumulative incidence can potentially be up to 2.3-2.6 times greater than abovementioned estimates. CONCLUSIONS: Our estimate of approximately 32-41% cumulative infection risk from February 28 to July 3, 2021 is roughly consistent with other published estimates, and they can potentially be greater, given an exit screening before departure. The present study results suggest the potential utility of border entry screening data to backcalculate the incidence in countries with limited surveillance capacity owing to a major surge in infections.

Epidemiological impact of travel enhancement on the inter-prefectural importation dynamics of COVID-19 in Japan, 2020.

Mobility restrictions were widely practiced to reduce contact with others and prevent the spatial spread of COVID-19 infection. Using inter-prefectural mobility and epidemiological data, a statistical model was devised to predict the number of imported cases in each Japanese prefecture. The number of imported cases crossing prefectural borders in 2020 was predicted using inter-prefectural mobility rates based on mobile phone data and prevalence estimates in the origin prefectures. The simplistic model was quantified using surveillance data of cases with an inter-prefectural travel history. Subsequently, simulations were carried out to understand how imported cases vary with the mobility rate and prevalence at the origin. Overall, the predicted number of imported cases qualitatively captured the observed number of imported cases over time. Although Hokkaido and Okinawa are the northernmost and the southernmost prefectures, respectively, they were sensitive to differing prevalence rate in Tokyo and Osaka and the mobility rate. Additionally, other prefectures were sensitive to mobility change, assuming that an increment in the mobility rate was seen in all prefectures. Our findings indicate the need to account for the weight of an inter-prefectural mobility network when implementing countermeasures to restrict human movement. If the mobility rates were maintained lower than the observed rates, then the number of imported cases could have been maintained at substantially lower levels than the observed, thus potentially preventing the unnecessary spatial spread of COVID-19 in late 2020.

Habitual Mask Wearing as Part of COVID-19 Control in Japan: An Assessment Using the Self-Report Habit Index.

Although the Japanese government removed mask-wearing requirements in 2023, relatively high rates of mask wearing have continued in Japan. We aimed to assess psychological reasons and the strength of habitual mask wearing in Japan. An Internet-based cross-sectional survey was conducted with non-random participant recruitment. We explored the frequency of mask usage, investigating psychological reasons for wearing masks. A regression analysis examined the association between psychological reasons and the frequency of mask wearing. The habitual use of masks was assessed in the participant's most frequently visited indoor space and public transport using the self-report habit index. The principal component analysis with varimax rotation revealed distinct habitual characteristics. Among the 2640 participants surveyed from 6 to 9 February 2023, only 4.9% reported not wearing masks at all. Conformity to social norms was the most important reason for masks. Participants exhibited a slightly higher degree of habituation towards mask wearing on public transport compared to indoor spaces. The mask-wearing rate was higher in females than in males, and no significant difference was identified by age group. Daily mask wearing in indoor spaces was characterized by two traits (automaticity and behavioral frequency). A high mask-wearing frequency has been maintained in Japan during the social reopening transition period. Mask wearing has become a part of daily habit, especially on public transport, largely driven by automatic and frequent practice.

Protection against SARS-CoV-2 BA.4 and BA.5 subvariants via vaccination and natural infection: A modeling study.

With continuing emergence of new SARS-CoV-2 variants, understanding the proportion of the population protected against infection is crucial for public health risk assessment and decision-making and so that the general public can take preventive measures. We aimed to estimate the protection against symptomatic illness caused by SARS-CoV-2 Omicron variants BA.4 and BA.5 elicited by vaccination against and natural infection with other SARS-CoV-2 Omicron subvariants. We used a logistic model to define the protection rate against symptomatic infection caused by BA.1 and BA.2 as a function of neutralizing antibody titer values. Applying the quantified relationships to BA.4 and BA.5 using two different methods, the estimated protection rate against BA.4 and BA.5 was 11.3% (95% confidence interval [CI]: 0.01-25.4) (method 1) and 12.9% (95% CI: 8.8-18.0) (method 2) at 6 months after a second dose of BNT162b2 vaccine, 44.3% (95% CI: 20.0-59.3) (method 1) and 47.3% (95% CI: 34.1-60.6) (method 2) at 2 weeks after a third BNT162b2 dose, and 52.3% (95% CI: 25.1-69.2) (method 1) and 54.9% (95% CI: 37.6-71.4) (method 2) during the convalescent phase after infection with BA.1 and BA.2, respectively. Our study indicates that the protection rate against BA.4 and BA.5 are significantly lower compared with those against previous variants and may lead to substantial morbidity, and overall estimates were consistent with empirical reports. Our simple yet practical models enable prompt assessment of public health impacts posed by new SARS-CoV-2 variants using small sample-size neutralization titer data to support public health decisions in urgent situations.

Go To Travel campaign and the geographic spread of COVID-19 in Japan.

BACKGROUND: In 2020, the Japanese government implemented first of two Go To Travel campaigns to promote the tourism sector as well as eating and drinking establishments, especially in remote areas. The present study aimed to explore the relationship between enhanced travel and geographic propagation of COVID-19 across Japan, focusing on the second campaign with nationwide large-scale economic boost in 2020. METHODS: We carried out an interrupted time-series analysis to identify the possible cause-outcome relationship between the Go To Travel campaign and the spread of infection to nonurban areas in Japan. Specifically, we counted the number of prefectures that experienced a weekly incidence of three, five, and seven COVID-19 cases or more per 100,000 population, and we compared the rate of change before and after the campaign. RESULTS: Three threshold values and three different models identified an increasing number of prefectures above the threshold, indicating that the inter-prefectural spread intensified following the launch of the second Go To Travel campaign from October 1st, 2020. The simplest model that accounted for an increase in the rate of change only provided the best fit. We estimated that 0.24 (95% confidence interval 0.15 to 0.34) additional prefectures newly exceeded five COVID-19 cases per 100,000 population per week during the second campaign. CONCLUSIONS: The enhanced movement resulting from the Go To Travel campaign facilitated spatial spread of COVID-19 from urban to nonurban locations, where health-care capacity may have been limited.

Doubling time of infectious diseases.

The concept of doubling time has been increasingly used since the onset of the coronavirus disease 2019 (COVID-19) pandemic, but its characteristics are not well understood, especially as applied to infectious disease epidemiology. The present study aims to be a practical guide to monitoring the doubling time of infectious diseases. Via simulation exercise, we clarify the epidemiological characteristics of doubling time, allowing possible interpretations. We show that the commonly believed relationship between the doubling time and intrinsic growth rate in population ecology does not strictly apply to infectious diseases, and derive the correct relationship between the two. We examined the impact of varying (i) the growth rate, (ii) the starting point of counting cumulative number of cases, and (iii) the length of observation on statistical estimation of doubling time. It was difficult to recover values of growth rate from doubling time, especially when the growth rate was small. Starting time period is critical when the statistical estimation of doubling time occurs during the course of an epidemic. The length of observation was critical in determining the overall magnitude of doubling time, and when only the latest 1-2 weeks' data were used, the resulting doubling time was very short, regardless of the intrinsic growth rate r. We suggest that doubling time estimates of infectious disease epidemics should at a minimum be accompanied by descriptions of (i) the starting time at which the cumulative count is initiated and (ii) the length of observation.

Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021.

Background: Public health and social measures (PHSM) against COVID-19 in Japan involve requesting the public to voluntarily reduce social contact; these measures are not legally binding. The effectiveness of such PHSM has been questioned with emergence of the SARS-CoV-2 Alpha variant (B.1.1.7), which exhibited elevated transmissibility. Materials and Methods: We investigated the epidemic dynamics during the fourth epidemic wave in Japan from March to June 2021 involving pre-emergency measures and declaration of a state of emergency (SoE). We estimated the effective reproduction number (R t ) before and after these interventions, and then analyzed the relationship between lower R t values and each PHSM. Results: With implementation of pre-emergency measures (PEM) in 16 prefectures, the R t was estimated to be < 1 in six prefectures; its average relative reduction ranged from 2 to 19%. During the SoE, 8 of 10 prefectures had an estimated R t < 1, and the average relative reduction was 26%-39%. No single intervention was identified that uniquely resulted in an R t value < 1. Conclusion: An SoE can substantially reduce the R t and may be required to curb a surge in cases caused by future SARS-CoV-2 variants of concern with elevated transmissibility. More customized interventions did not reduce the R t value to < 1 in this study, but that may be partly attributable to the greater transmissibility of the Alpha variant.

Phenomenological and mechanistic models for predicting early transmission data of COVID-19.

Forecasting future epidemics helps inform policy decisions regarding interventions. During the early coronavirus disease 2019 epidemic period in January-February 2020, limited information was available, and it was too challenging to build detailed mechanistic models reflecting population behavior. This study compared the performance of phenomenological and mechanistic models for forecasting epidemics. For the former, we employed the Richards model and the approximate solution of the susceptible-infected-recovered (SIR) model. For the latter, we examined the exponential growth (with lockdown) model and SIR model with lockdown. The phenomenological models yielded higher root mean square error (RMSE) values than the mechanistic models. When using the numbers from reported data for February 1 and 5, the Richards model had the highest RMSE, whereas when using the February 9 data, the SIR approximation model was the highest. The exponential model with a lockdown effect had the lowest RMSE, except when using the February 9 data. Once interventions or other factors that influence transmission patterns are identified, they should be additionally taken into account to improve forecasting.

"Go To Travel" Campaign and Travel-Associated Coronavirus Disease 2019 Cases: A Descriptive Analysis, July-August 2020.

The Japanese government initiated the Go To Travel campaign on 22 July 2020, offering deep discounts on hotel charges and issuing coupons to be used for any consumption at travel destinations in Japan. In the present study, we aimed to describe the possible epidemiological impact of the tourism campaign on increasing travel-associated cases of coronavirus disease 2019 (COVID-19) in the country. We compared the incidence rates of travel-associated and tourism-related cases prior to and during the campaign. The incidence of travel-associated COVID-19 cases during the tourism campaign was approximately three times greater than the control period 22 June to 21 July 2020 and approximately 1.5 times greater than the control period of 15 to 19 July. The incidence owing to tourism was approximately 8 times and 2-3 times greater than the control periods of 22 June to 21 July and 15 to 19 July, respectively. Although the second epidemic wave in Japan had begun to decline by mid-August, enhanced domestic tourism may have contributed to increasing travel-associated COVID-19 cases during 22 to 26 July, the early stage of the Go To Travel campaign.

Relative Reproduction Number of SARS-CoV-2 Omicron (B.1.1.529) Compared with Delta Variant in South Africa.

The world identified the rapidly increasing incidence of the causative variant of SARS-CoV-2 Pangolin B [...].

Containment, Contact Tracing and Asymptomatic Transmission of Novel Coronavirus Disease (COVID-19): A Modelling Study.

When a novel infectious disease emerges, enhanced contact tracing and isolation are implemented to prevent a major epidemic, and indeed, they have been successful for the control of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), which have been greatly reduced without causing a global pandemic. Considering that asymptomatic and pre-symptomatic infections are substantial for the novel coronavirus disease (COVID-19), the feasibility of preventing the major epidemic has been questioned. Using a two-type branching process model, the present study assesses the feasibility of containing COVID-19 by computing the probability of a major epidemic. We show that if there is a substantial number of asymptomatic transmissions, cutting chains of transmission by means of contact tracing and case isolation would be very challenging without additional interventions, and in particular, untraced cases contribute to lowering the feasibility of containment. Even if isolation of symptomatic cases is conducted swiftly after symptom onset, only secondary transmissions after the symptom onset can be prevented.

Assessing the Impact of Reduced Travel on Exportation Dynamics of Novel Coronavirus Infection (COVID-19).

The impact of the drastic reduction in travel volume within mainland China in January and February 2020 was quantified with respect to reports of novel coronavirus (COVID-19) infections outside China. Data on confirmed cases diagnosed outside China were analyzed using statistical models to estimate the impact of travel reduction on three epidemiological outcome measures: (i) the number of exported cases, (ii) the probability of a major epidemic, and (iii) the time delay to a major epidemic. From 28 January to 7 February 2020, we estimated that 226 exported cases (95% confidence interval: 86,449) were prevented, corresponding to a 70.4% reduction in incidence compared to the counterfactual scenario. The reduced probability of a major epidemic ranged from 7% to 20% in Japan, which resulted in a median time delay to a major epidemic of two days. Depending on the scenario, the estimated delay may be less than one day. As the delay is small, the decision to control travel volume through restrictions on freedom of movement should be balanced between the resulting estimated epidemiological impact and predicted economic fallout.

Communicating the Risk of Death from Novel Coronavirus Disease (COVID-19).

To understand the severity of infection for a given disease, it is common epidemiological practice to estimate the case fatality risk, defined as the risk of death among cases. However, there are three technical obstacles that should be addressed to appropriately measure this risk. First, division of the cumulative number of deaths by that of cases tends to underestimate the actual risk because deaths that will occur have not yet observed, and so the delay in time from illness onset to death must be addressed. Second, the observed dataset of reported cases represents only a proportion of all infected individuals and there can be a substantial number of asymptomatic and mildly infected individuals who are never diagnosed. Third, ascertainment bias and risk of death among all those infected would be smaller when estimated using shorter virus detection windows and less sensitive diagnostic laboratory tests. In the ongoing COVID-19 epidemic, health authorities must cope with the uncertainty in the risk of death from COVID-19, and high-risk individuals should be identified using approaches that can address the abovementioned three problems. Although COVID-19 involves mostly mild infections among the majority of the general population, the risk of death among young adults is higher than that of seasonal influenza, and elderly with underlying comorbidities require additional care.

Reconstructing the population dynamics of foreign residents in Japan to estimate the prevalence of infection with Mycobacterium tuberculosis.

Among newly notified tuberculosis cases in Japan, both the number and the proportion of foreign-born cases have steadily increased over time. As Japan prepares to introduce pre-entry tuberculosis screening for foreign-born persons entering Japan, various epidemiological evidence is needed to evaluate its effectiveness, including the prevalence of tuberculosis among current foreign residents in Japan, by country of birth. Yet as of today, even the underlying population dynamics has yet to be quantified. The present study therefore aimed to firstly reconstruct the demographic prevalence of foreign residents by the length of stay in Japan and by country of birth, and secondly, to estimate the prevalence of infection from notification data among foreign residents in Japan. We employed the McKendrick partial differential equation model to reconstruct the dynamics among six Asian countries which account for 80% of foreign-born tuberculosis patients notified in Japan i.e. China, the Philippines, Vietnam, Nepal, Indonesia, and Myanmar. Compared with China and the Philippines, the recent remarkable increase in the number of residents who had arrived within 5 years from Myanmar and Vietnam was identified. Assuming that the risk of primary tuberculosis given infection is 5%, the estimated prevalence of infection ranged from 3.5% to 21.3%, and all the estimates were more than three times greater than the crude estimate that ignored the time since immigration. The proposed method may be used to further estimate the prevalence by age, sex and residential status, which could potentially provide critical evidence towards establishing policies to control tuberculosis among foreign-born persons in Japan, and also possibly among migrants globally.