Modelling the Risk of Imported COVID-19 Infections at Maritime Ports Based on the Mobility of International-Going Ships

Maritime ports are critical logistics hubs that play an important role when preventing the transmission of COVID-19-imported infections from incoming international-going ships. This study introduces a data-driven method to dynamically model infection risks of international ports from imported COVID-19 cases. The approach is based on global Automatic Identification System (AIS) data and a spatio-temporal clustering algorithm that both automatically identifies ports and countries approached by ships and correlates them with country COVID-19 statistics and stopover dates. The infection risk of an individual ship is firstly modeled by considering the current number of COVID-19 cases of the approached countries, increase rate of the new cases, and ship capacity. The infection risk of a maritime port is mainly calculated as the aggregation of the risks of all of the ships stopovering at a specific date. This method is applied to track the risk of the imported COVID-19 of the main cruise ports worldwide. The results show that the proposed method dynamically estimates the risk level of the overseas imported COVID-19 of cruise ports and has the potential to provide valuable support to improve prevention measures and reduce the risk of imported COVID-19 cases in seaports.

Strategies to reduce the risk of SARS-CoV-2 importation from international travellers: modelling estimations for the United Kingdom, July 2020

Background To mitigate SARS-CoV-2 transmission risks from international air travellers, many countries implemented a combination of up to 14 days of self-quarantine upon arrival plus PCR testing in the early stages of the COVID-19 pandemic in 2020. Aim To assess the effectiveness of quarantine and testing of international travellers to reduce risk of onward SARS-CoV-2 transmission into a destination country in the pre-COVID-19 vaccination era. Methods We used a simulation model of air travellers arriving in the United Kingdom from the European Union or the United States, incorporating timing of infection stages while varying quarantine duration and timing and number of PCR tests. Results Quarantine upon arrival with a PCR test on day 7 plus a 1-day delay for results can reduce the number of infectious arriving travellers released into the community by a median 94% (95% uncertainty interval (UI): 89–98) compared with a no quarantine/no test scenario. This reduction is similar to that achieved by a 14-day quarantine period (median > 99%; 95% UI: 98–100). Even shorter quarantine periods can prevent a substantial amount of transmission; all strategies in which travellers spend at least 5 days (mean incubation period) in quarantine and have at least one negative test before release are highly effective (median reduction 89%; 95% UI: 83–95)). Conclusion The effect of different screening strategies impacts asymptomatic and symptomatic individuals differently. The choice of an optimal quarantine and testing strategy for unvaccinated air travellers may vary based on the number of possible imported infections relative to domestic incidence.

A PCR-Based Technique to Track the Geographic Origin of Plasmodium falciparum With 23-SNP Barcode Analysis

Increased population movement has increased the risk of reintroducing parasites to elimination areas and also dispersing drug-resistant parasites to new regions. Therefore, reliable and repeatable methods to trace back to the source of imported infections are essential. The recently developed 23-single-nucleotide polymorphism (SNP) barcode from organellar genomes of mitochondrion (mt) and apicoplast (apico) provides a valuable tool to locate the geographic origin of Plasmodium falciparum. This study aims to explore the feasibility of using the 23-SNP barcode for tracking P. falciparum by polymerase chain reaction and sequencing, while providing geographical haplotypes of isolates that originated from Central Africa. Based on 23-SNP barcode analysis, SNPs were found at seven loci; 27 isolates were confirmed to have originated in West Africa, and this study also showed four isolates from Central Africa (Equatorial Guinea, 3; Republic of Congo, 1) that originated in East Africa. This study provides the sequence data from Central Africa and fills 23-SNP barcode data gaps of sample origins.

The first laboratory-confirmed imported infections of SARS-CoV-2 in Sudan

Background The rapidly growing pandemic of coronavirus disease 2019 (COVID-19) has challenged health systems globally. Here we report the first identified infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; aetiology of COVID-19) among recent international arrivals to Sudan and their contacts. Methods Suspected cases were identified clinically and/or epidemiologically. Samples from suspected cases and their contacts were tested in the National Influenza Centre following World Health Organization protocols. Two real-time reverse transcription quantitative polymerase chain reaction assays were used to detect and confirm SARS-CoV-2 infection. Results Seven cases of COVID-19, including two deaths, were confirmed in Sudan between 27 February and 30 March 2020. Suspected cases were identified and tested. As of 30 March, no local transmission was yet reported in the country. Fifty-nine percent of the suspected cases were international travellers coming from areas with current COVID-19 epidemics. Cough and fever were the major symptoms, presented by 65% and 60% of the suspected cases, respectively. By early April, an additional seven cases were confirmed through limited contact tracing that identified the first locally acquired infections in recent contact with imported cases. Conclusions The high mortality rate of COVID-19 cases in Sudan might be due to limitations in test and trace and case management services. Unfortunately, infections have spread further into other states and the country has no capacity for mass community screening to better estimate disease prevalence. Therefore external support is urgently needed to improve the healthcare and surveillance systems.

Epidemiology of imported infectious diseases, China, 2014–18

Background The frequent movement of population between countries brings an increasing number of travel-related infections. This study aims to define the spectrum and dynamics of imported infections observed from international travel in the Chinese mainland. Methods Sick travellers were screened by inbound sentinel surveillance and post-travel clinic visits from 2014 to 18. The infections were classified as respiratory, gastrointestinal, vector-borne, blood/sexually transmitted and mucocutaneous. The analysed variables included the place of origin of the travellers (Chinese or foreign) and the time when travel-related infection was present (at the time of return, during travel and post-travel visits to the clinic). Results In total, 58 677 cases were identified amongst 1 409 265 253 travellers, with an incidence of 41.64/million, comprising during-travel incidence of 27.44/million and a post-travel incidence of 14.20/million. Respiratory infections constituted the highest proportion of illnesses during travel (81.19%, 31 393 of 38 667), which mainly came from Asian countries and tourists; with influenza virus and rhinovirus infections being mainly diagnosed. Vector-borne diseases constituted the highest proportion of post-travel illnesses (98.14%, 19 638 of 20 010), which were mainly diagnosed from African countries and labourers; with malaria and dengue fever being mainly diagnosed. The differential infection spectrum varied in terms of the traveller’s demography, travel destination and travel purpose. As such, a higher proportion of foreign travellers had blood/sexually transmitted diseases (89.85%, 2832 of 3152), while Chinese citizens had a higher prevalence of vector-borne diseases (85.98%, 19 247 of 22 387) and gastrointestinal diseases (79.36%, 1115 of 1405). The highest incidence rate was observed amongst travellers arriving from Africa, while the lowest was observed amongst travellers arriving from Europe. Conclusions The findings might help in preparing recommendations for travellers and also aid in primary care or other clinics that prepare travellers before trips abroad. The findings will also help to identify locations and the associated types of infections that might require attention.

Genetic evidence for imported malaria and local transmission in Richard Toll, Senegal

Background Malaria elimination efforts can be undermined by imported malaria infections. Imported infections are classified based on travel history. Methods A genetic strategy was applied to better understand the contribution of imported infections and to test for local transmission in the very low prevalence region of Richard Toll, Senegal. Results Genetic relatedness analysis, based upon molecular barcode genotyping data derived from diagnostic material, provided evidence for both imported infections and ongoing local transmission in Richard Toll. Evidence for imported malaria included finding that a large proportion of Richard Toll parasites were genetically related to parasites from Thiès, Senegal, a region of moderate transmission with extensive available genotyping data. Evidence for ongoing local transmission included finding parasites of identical genotype that persisted across multiple transmission seasons as well as enrichment of highly related infections within the households of non-travellers compared to travellers. Conclusions These data indicate that, while a large number of infections may have been imported, there remains ongoing local malaria transmission in Richard Toll. These proof-of-concept findings underscore the value of genetic data to identify parasite relatedness and patterns of transmission to inform optimal intervention selection and placement.

Repeat SARS-CoV-2 Testing Models for Residential College Populations

Residential colleges are considering re-opening under uncertain futures regarding the COVID-19 pandemic. We consider repeat SARS-CoV-2 testing models for the purpose of containing outbreaks in the residential campus community. The goal of repeat testing is to detect and isolate new infections rapidly to block transmission that would otherwise occur both on and off campus. The models allow for specification of aspects including scheduled on-campus resident screening at a given frequency, test sensitivity that can depend on the time since infection, imported infections from off campus throughout the school term, and a lag from testing until student isolation due to laboratory turnaround and student relocation delay. For early- (late-) transmission of SARS-CoV-2 by age of infection, we find that weekly screening cannot reliably contain outbreaks with reproductive numbers above 1.4 (1.6) if more than one imported exposure per 10,000 students occurs daily. Screening every three days can contain outbreaks providing the reproductive number remains below 1.75 (2.3) if transmission happens earlier (later) with time from infection, but at the cost of increased false positive rates requiring more isolation quarters for students testing positive. Testing frequently while minimizing the delay from testing until isolation for those found positive are the most controllable levers for preventing large residential college outbreaks. A web app that implements model calculations is available to facilitate exploration and consideration of a variety of scenarios.

Estimating the establishment of local transmission and the cryptic phase of the COVID-19 pandemic in the USA

We use a global metapopulation transmission model to study the establishment of sustained and undetected community transmission of the COVID-19 epidemic in the United States. The model is calibrated on international case importations from mainland China and takes into account travel restrictions to and from international destinations. We estimate widespread community transmission of SARS-CoV-2 in February, 2020. Modeling results indicate international travel as the key driver of the introduction of SARS-CoV-2 in the West and East Coast metropolitan areas that could have been seeded as early as late-December, 2019. For most of the continental states the largest contribution of imported infections arrived through domestic travel flows.

Genetic evidence for imported malaria and local transmission in Richard Toll, Senegal

Background: Malaria elimination efforts can be undermined by imported malaria infections. Imported infections are classified based on travel history. Methods: We applied a genetic strategy to better understand the contribution of imported infections and to test for local transmission in the very low prevalence region of Richard Toll, Senegal. Results: Genetic relatedness analysis, based upon molecular barcode genotyping data derived from diagnostic material, provided evidence for both imported infections and ongoing local transmission in Richard Toll. Evidence for imported malaria included finding that a large proportion of Richard Toll parasites were genetically related to parasites from Thiès, Senegal, a region of moderate transmission with extensive available genotyping data. Evidence for ongoing local transmission included finding parasites of identical genotype that persisted across multiple transmission seasons as well as enrichment of highly related infections within the households of non-travelers compared to travelers. Conclusions: These data indicate that, while a large number of infections may have been imported, there remains ongoing local malaria transmission in Richard Toll. These proof-of-concept findings underscore the value of genetic data to identify parasite relatedness and patterns of transmission to inform optimal intervention selection and placement.

Evaluating the effectiveness of countermeasures to control the novel coronavirus disease 2019 in Jilin Province, China

Objective: This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of countermeasures to control the disease in Jilin Province, China.Methods: The data of reported COVID-19 cases were collected, including imported and local cases from Jilin Province as of March 14, 2019. A Susceptible–Exposed–Infectious–Asymptomatic–Recovered (SEIAR) model was developed to fit the data, and the effective reproduction number (Reff) was calculated at different stages in the province. Finally, the effectiveness of the countermeasures was assessed. Results: A total of 97 COVID-19 infections were reported in Jilin Province, among which 45 were imported infections (including one asymptomatic infection) and 52 were local infections (including three asymptomatic infections). The model fit well with the reported data (R2 = 0.593, P < 0.001). The Reff of COVID-19 before and after February 1, 2020 was 1.64 and 0.05, respectively. Without the intervention taken on February 1, 2020, the predicted cases would reach a peak of 177011 on October 22, 2020 (384 days from the first case), and 17129367 cases would be reported until the end of the outbreak (on October 9, 2021), with a total attack rate of 63.66%. These results revealed that the interventions implemented in Jilin Province had reduced more than 99.99% cases.Conclusions: COVID-19 has a moderate transmissibility in Jilin Province, China. The interventions implemented in the province had great effectiveness.