Secondary attack rates and determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) household transmission in Pakistan: A case-ascertained prospective, longitudinal study

BACKGROUND

Households are considered ideal settings for studying the transmission dynamics of an infectious disease.

METHODS

A prospective study was conducted, based on the World Health Organization FFX protocol from October 2020 to January,2021. Household contacts of laboratory-confirmed index cases were followed up for their symptomatic history, nasal swabs for RT-PCR,and blood samples for anti-SARS CoV-2 antibodies were collected at enrollment and days 7, 14 and 28. We estimated secondary attack rate (SAR), effective household case cluster size and determinants of secondary infection among susceptible household contacts using multivariable logistic regression.

RESULTS

We enrolled 77 index cases and their 543 contacts. Out of these, 252 contacts were susceptible at the time of enrollment. There were 77 household clusters, out of which, transmission took place in 20 (25.9%) giving rise to 34 cases. The acquired secondary attack rate (SAR) was 14.0% (95% CI 9.0-18.0). The effective household case cluster size was 0.46 (95%CI 0.33,0.56). Reported symptoms of nausea and vomiting (aOR, 7.9; 95% CI, 1.4-45.5) and fatigue (aOR, 9.3; 95% CI, 3.8-22.7) were associated with SARS-CoV-2 transmission.

CONCLUSIONS

We observed a low SARS-CoV-2 secondary attack rate in the backdrop of high seroprevalence and asymptomatic transmission among households in Karachi, Pakistan.

Combining wastewater surveillance and case data in estimating the time-varying effective reproduction number

Wastewater surveillance has been increasingly acknowledged as a useful tool for monitoring transmission dynamics of infections of public health concern, including the coronavirus disease (COVID-19). While a range of models have been proposed to estimate the time-varying effective reproduction number (Rt) utilizing clinical data, few have harnessed the viral concentration in wastewater samples to do so, leaving uncertainties about the potential precision gains with its use. In this study, we developed a Bayesian hierarchical model which simultaneously reconstructed the latent infection trajectory and estimated Rt. Focusing on the 2022 and early 2023 COVID-19 transmission trends in Singapore, where mass community wastewater surveillance has become routine, we performed estimations using a spectrum of data sources, including reported case counts, hospital admissions, deaths, and wastewater viral loads. We further explored the performance of our wastewater model across various scenarios with different sampling strategies. The results showed consistent estimates derived from models employing diverse data streams, while models incorporating more wastewater samples exhibited greater uncertainty and variation in the inferred Rts. Additionally, our analysis revealed prominent day-of-the-week effect in reported case counts and substantial temporal variations in ascertainment rates. In response to these findings, we advocate for a hybrid approach leveraging both clinical and wastewater surveillance data to account for changes in case-ascertainment rates. Furthermore, our study demonstrates the possibility of reducing sampling frequency or sample size without compromising estimation accuracy for Rt, highlighting the potential for optimizing resource allocation in surveillance efforts while maintaining robust insights into the transmission dynamics of infectious diseases.

Expansion and transmission dynamics of high risk carbapenem-resistant Klebsiella pneumoniae subclones in China: An epidemiological, spatial, genomic analysis

AIMS

Carbapenem-resistant Klebsiella pneumonia (CRKP) is a global threat that varies by region. The global distribution, evolution, and clinical implications of the ST11 CRKP clone remain obscure.

METHODS

We conducted a multicenter molecular epidemiological survey using isolates obtained from 28 provinces and municipalities across China between 2011 and 2021. We integrated sequences from public databases and performed genetic epidemiology analysis of ST11 CRKP.

RESULTS

Among ST11 CRKP, KL64 serotypes exhibited considerable expansion, increasing from 1.54% to 46.08% between 2011 and 2021. Combining our data with public databases, the phylogenetic and phylogeography analyses indicated that ST11 CRKP appeared in the Americas in 1996 and spread worldwide, with key clones progressing from China's southeastern coast to the inland by 2010. Global phylogenetic analysis showed that ST11 KL64 CRKP has evolved to a virulent, resistant clade with notable regional spread. Single-nucleotide polymorphism (SNP) analysis identified BMPPS (bmr3, mltC, pyrB, ppsC, and sdaC) as a key marker for this clade. The BMPPS SNP clade is associated with high mortality and has strong anti-phagocytic and competitive traits in vitro.

CONCLUSIONS

The high-risk ST11 KL64 CRKP subclone showed strong expansion potential and survival advantages, probably owing to genetic factors.

Transmission dynamics of Zika virus with multiple infection routes and a case study in Brazil

The Zika virus (ZIKV) is a serious global public health crisis. A major control challenge is its multiple transmission modes. This paper aims to simulate the transmission patterns of ZIKV using a dynamic process-based epidemiological model written in ordinary differential equations, which incorporates the human-to-mosquito infection by bites and sewage, mosquito-to-human infection by bites, and human-to-human infection by sex. Mathematical analyses are carried out to calculate the basic reproduction number and backward bifurcation, and prove the existence and stability of the equilibria. The model is validated with infection data by applying it to the 2015-2016 ZIKV epidemic in Brazil. The results indicate that the reproduction number is estimated to be 2.13, in which the contributions by mosquito bite, sex and sewage account for 85.7%, 3.5% and 10.8%, respectively. This number and the morbidity rate are most sensitive to parameters related to mosquito ecology, rather than asymptomatic or human-to-human transmission. Multiple transmission routes and suitable temperature exacerbate ZIKV infection in Brazil, and the vast majority of human infection cases were prevented by the intervention implemented. These findings may provide new insights to improve the risk assessment of ZIKV infection.

Data-driven mechanistic framework with stratified immunity and effective transmissibility for COVID-19 scenario projections

Scenario-based modeling frameworks have been widely used to support policy-making at state and federal levels in the United States during the COVID-19 response. While custom-built models can be used to support one-off studies, sustained updates to projections under changing pandemic conditions requires a robust, integrated, and adaptive framework. In this paper, we describe one such framework, UVA-adaptive, that was built to support the CDC-aligned Scenario Modeling Hub (SMH) across multiple rounds, as well as weekly/biweekly projections to Virginia Department of Health (VDH) and US Department of Defense during the COVID-19 response. Building upon an existing metapopulation framework, PatchSim, UVA-adaptive uses a calibration mechanism relying on adjustable effective transmissibility as a basis for scenario definition while also incorporating real-time datasets on case incidence, seroprevalence, variant characteristics, and vaccine uptake. Through the pandemic, our framework evolved by incorporating available data sources and was extended to capture complexities of multiple strains and heterogeneous immunity of the population. Here we present the version of the model that was used for the recent projections for SMH and VDH, describe the calibration and projection framework, and demonstrate that the calibrated transmissibility correlates with the evolution of the pathogen as well as associated societal dynamics.

Spatio-temporal ditribution and transmission dynamics of sheep pox and goat pox diseases in South Wollo zone north East Ethiopia

Sheep pox (SP) and goat pox diseases (GP) are highly transmittable, malignant systemic and economically significant caused by the genus Capripoxvirus. using The spatio-temporal distribution of SP and GP outbreaks in South Wollo zone from September 2013 to December 2019 was determined retrospectively using SP and GP outbreaks report Kombolcha regional laboratory. A follow up study was also conducted from December 2019 to March 2021 to estimate the transmission parameter of SP and GP outbreaks in South Wollo zone of Kutaber district, Amhara region. Tissue samples from outbreaks in Kundi and Haroye kebele of Kutaber district were taken to confirm the outbreak by conventional polymerase chain reaction (PCR). The transmission parameters were estimated using Generalized linear model (GLM) based on stochastic Susceptible Infected and Recovered (SIR) model. In South Wollo zone, 249 SGP outbreaks were reported from 2013 to 2019. The incidence differed between months, with a highest peak in October and November and a lowest peak in February. The basic reproduction ratios (R0) of the SGP disease outbreaks were 1.84 and 3 for Haroye and Kundi kebele outbreaks, respectively. The disease is distributed throughout the zone and the investigated active outbreaks had moderate transmission between animals. Hence, it needs a great effort which focuses on the application of control measures that reduce the transmission of the disease.

Predicting consequences of COVID-19 control measure de-escalation on nosocomial transmission and mortality: a modelling study in a French rehabilitation hospital

INTRODUCTION

Infection control measures are effective for nosocomial COVID-19 prevention but bear substantial health-economic costs, motivating their "de-escalation" in settings at low risk of SARS-CoV-2 transmission. Yet consequences of de-escalation are difficult to predict, particularly in light of novel variants and heterogeneous population immunity.

AIM

To estimate how infection control measure de-escalation influences nosocomial COVID-19 risk.

METHODS

An individual-based transmission model was used to simulate SARS-CoV-2 outbreaks and control measure de-escalation in a French long-term care hospital with multi-modal control measures in place (testing and isolation, universal masking, single-occupant rooms). Estimates of COVID-19 case fatality rates (CFRs) from reported outbreaks were used to quantify excess COVID-19 mortality due to de-escalation.

RESULTS

In a population fully susceptible to infection, de-escalating both universal masking and single rooms resulted in hospital-wide outbreaks of 114 (95% CI: 103-125) excess infections, compared with five (three to seven) excess infections when de-escalating only universal masking or 15 (11-18) when de-escalating only single rooms. When de-escalating both measures and applying CFRs from the first wave of COVID-19, excess patient mortality ranged from 1.57 (1.41-1.71) to 9.66 (8.73-10.57) excess deaths/1000 patient-days. By contrast, when applying CFRs from subsequent pandemic waves and assuming susceptibility to infection among 40-60% of individuals, excess mortality ranged from 0 (0-0) to 0.92 (0.77-1.07) excess deaths/1000 patient-days.

CONCLUSIONS

The de-escalation of bundled COVID-19 control measures may facilitate widespread nosocomial SARS-CoV-2 transmission. However, excess mortality is probably limited in populations at least moderately immune to infection and given CFRs resembling those estimated during the 'post-vaccine' era.

Foot and mouth disease viruses are recurrently introduced to Israel and spread by extensively reared sheep and cattle: Insights from a whole-genome sequence analysis

Despite routine vaccination, Israel experiences recurrent outbreaks of foot and mouth disease (FMD). We analyzed VP1 coding sequences of viruses isolated during FMD outbreaks from 2001 to 2011 in Israel and neighboring nations. The Israeli strains were aligned with strains from neighboring countries in corresponding years, implying repeated FMD virus incursions. In 2007 a large FMD epidemic, caused by a serotype O virus, occurred in Israel. Bayesian analysis of whole-genome sequences of viruses isolated during this epidemic revealed predominant transmission among extensively farmed beef-cattle and small ruminants. Small ruminants were key in spreading to beef-cattle, which then transmitted the virus to feedlot-cattle. Wild gazelles had a minor role in transmission. The results may suggest probable transmission of FMD virus from the Palestinian Authority to Israel. Targeting extensive farms via enhanced surveillance and vaccination could improve FMDV control. Given cross-border transmission, a collaborative FMD mitigation strategy across the Middle-East is crucial.

A compartmental model for Schistosoma japonicum transmission dynamics in the Philippines

Schistosomiasis is a chronic and debilitating neglected tropical disease (NTD), second only to malaria as one of the most devastating parasitic diseases. Caused by a parasitic flatworm of the genus Schistosoma, infection occurs when skin comes in contact with contaminated freshwater that contains schistosome-hosting snails. The disease continues to be endemic in many regions of the Philippines, where it poses a significant public health challenge due to a lack of healthcare resources. In the Philippines, additional mammalian reservoirs for the S. japonicum parasite, especially bovines such as carabaos, also facilitate the spread of schistosomiasis. We extend existing compartment models to include human, snail, bovine, and free-living Schistosoma for a comprehensive look at the transmission dynamics of the disease. Sensitivity analysis of model parameters shows that the carabaos themselves can sustain the endemicity of schistosomiasis. Thus, we consider the control method of farming mechanization to avoid contaminated freshwater sources. We find that a reduction of contaminated water contacts by at least 77% will break the transmission cycle and eliminate the disease. However, reducing the contact by about 70% will still result in decrease of human schistosomiasis prevalence to under 1% in 15 years or less. Achieving such high reduction of contact rates could be a daunting task, especially in rural areas. Still, the potential to eliminate or at least reduce the schistosomiasis prevalence should be considered an additional benefit of mechanization efforts in the Philippines.

Model-based analysis of the incidence trends and transmission dynamics of COVID-19 associated with the Omicron variant in representative cities in China

BACKGROUND

In 2022, Omicron outbreaks occurred at multiple sites in China. It is of great importance to track the incidence trends and transmission dynamics of coronavirus disease 2019 (COVID-19) to guide further interventions.

METHODS

Given the population size, economic level and transport level similarities, two groups of outbreaks (Shanghai vs. Chengdu and Sanya vs. Beihai) were selected for analysis. We developed the SEAIQRD, ARIMA, and LSTM models to seek optimal modeling techniques for waves associated with the Omicron variant regarding data predictive performance and mechanism transmission dynamics, respectively. In addition, we quantitatively modeled the impacts of different combinations of more stringent interventions on the course of the epidemic through scenario analyses.

RESULTS

The best-performing LSTM model showed better prediction accuracy than the best-performing SEAIQRD and ARIMA models in most cases studied. The SEAIQRD model had an absolute advantage in exploring the transmission dynamics of the outbreaks. Regardless of the time to inflection point or the time to Rt curve below 1.0, Shanghai was later than Chengdu (day 46 vs. day 12/day 54 vs. day 14), and Sanya was later than Beihai (day 16 vs. day 12/day 20 vs. day 16). Regardless of the number of peak cases or the cumulative number of infections, Shanghai was higher than Chengdu (34,350 vs. 188/623,870 vs. 2,181), and Sanya was higher than Beihai (1,105 vs. 203/16,289 vs. 3,184). Scenario analyses suggested that upgrading control level in advance, while increasing the index decline rate and quarantine rate, were of great significance for shortening the time to peak and Rt below 1.0, as well as reducing the number of peak cases and final affected population.

CONCLUSIONS

The LSTM model has great potential for predicting the prevalence of Omicron outbreaks, whereas the SEAIQRD model is highly effective in revealing their internal transmission mechanisms. We recommended the use of joint interventions to contain the spread of the virus.

COVID-19 transmission driven by age-group mathematical model in Shijiazhuang City of China

Background

A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination, host, and non-pharmaceutical interventions (NPIs). Herein, we investigated the epidemiological characteristics of all reported symptomatic cases by picking Shijiazhuang City, Hebei Province in Northern China as research objective. In addition, we established a with age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three scenarios.

Methods

All reported symptomatic cases of Shijiazhuang epidemic (January 2-February 3, 2021) were investigated in our study. The cases were classified by gender, age group and location, the distributions were analyzed by epidemiological characteristics. Furthermore, the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three scenarios.

Results

Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11, 2021, which was implemented with strong NPIs by local government and referred as baseline situation in this study. The research results showed that R0 under baseline situation ranged from 4.47 to 7.72, and Rt of Gaocheng Distinct took 3.72 with 95% confidence interval from 3.23 to 4.35 on January 9, the declining tendencies of Rt under baseline situation were kept till February 3, the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang epidemic. This indicated Shijiazhuang epidemic was under control on January 19. However, if the strong NPIs were kept, but remote isolation operated on January 11 was not implemented as of February 9, then the scale of Shijiazhuang epidemic reached 9482 cases from age group who were 60 years old and over out of 31,017 symptomatic cases. The investigation also revealed that Shijiazhuang epidemic reached 132,648 symptomatic cases for age group who were 60 years old and over (short for G2) under risk-based strategies (Scenario A), 58,048 symptomatic cases for G2 under late quarantine strategies (Scenario B) and 207,124 symptomatic cases for G2 under late quarantine double risk strategies (Scenario C), and that the corresponding transmission tendencies of Rt for three scenarios were consistently controlled on Jan 29, 2021. Compared with baseline situation, the dates for controlling Rt below 1 under three scenarios were delayed 10 days.

Conclusions

Shijiazhuang epidemic was the first COVID-19 outbreak in the rural areas in Hebei Province of Northern China. The targeted interventions adopted in early 2021 were effective to halt the transmission due to the implementation of a strict and village-wide closure. However we found that age group profile and NPIs played critical rules to successfully contain Shijiazhuang epidemic, which should be considered by public health policies in rural areas of mainland China during the dynamic zero-COVID policy.

Microsatellite markers for Opisthorchis felineus to understand its genetic diversity and transmission patterns of opisthorchiosis

Opisthorchis felineus is a food-borne trematode which causes opisthorchiosis and affects mainly the liver and bile ducts of the liver with a possible risk of bile duct carcinogenesis resulting in cholangiocarcinoma. In Russia, O. felineus is mainly endemic in Western Siberia (Ob and Irtysh river basins) and occurs throughout the Volga, Kama, Don, and Dnepr river basins. The prevalence, intensity, and clinical significance of human infections and the incidence of cholangiocarcinoma vary geographically in endemic regions. Currently, there is substantial evidence on genetic variation of O. felineus, but information on the population genetic structure is so far very scarce. Because microsatellite DNA of this parasite is not available, we for the first time isolated sufficient microsatellite loci to examine the genetic diversity and population structure of O. felineus, using multiple nuclear loci approach. A total of ten highly polymorphic microsatellite loci from a constructed enriched genomic DNA library were characterized, using 29 samples representing huge O. felineus metapopulation extended in latitude over 5000 km from Middle Europe to Western Siberia. At least three populations can be discerned as result of analysis of the microsatellite loci genetic diversity. Based on the results for the first time, a hypothesis was put forward about the formation of a modern habitat of O. felineus.

EpiMix: A novel method to estimate effective reproduction number

Transmission potential of a pathogen, often quantified by the time-varying reproduction number Rt, provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control. In this study, we proposed a novel method, EpiMix, for Rt estimation, wherein we incorporated the impacts of exogenous factors and random effects under a Bayesian regression framework. Using Integrated Nested Laplace Approximation, EpiMix is able to efficiently generate reliable, deterministic Rt estimates. In the simulations and case studies performed, we further demonstrated the method's robustness in low-incidence scenarios, together with other merits, including its flexibility in selecting variables and tolerance of varying reporting rates. All these make EpiMix a potentially useful tool for real-time Rt estimation provided that the serial interval distribution, time series of case counts and external influencing factors are available.

Mathematical modeling for Delta and Omicron variant of SARS-CoV-2 transmission dynamics in Greece

A compartmental, epidemiological, mathematical model was developed in order to analyze the transmission dynamics of Delta and Omicron variant, of SARS-CoV-2, in Greece. The model was parameterized twice during the 4th and 5th wave of the pandemic. The 4th wave refers to the period during which the Delta variant was dominant (approximately July to December of 2021) and the 5th wave to the period during which the Omicron variant was dominant (approximately January to May of 2022), in accordance with the official data from the National Public Health Organization (NPHO). Fitting methods were applied to evaluate important parameters in connection with the transmission of the variants, as well as the social behavior of population during these periods of interest. Mathematical models revealed higher numbers of contagiousness and cases of asymptomatic disease during the Omicron variant period, but a decreased rate of hospitalization compared to the Delta period. Also, parameters related to the behavior of the population in Greece were also assessed. More specifically, the use of protective masks and the abidance of social distancing measures. Simulations revealed that over 5,000 deaths could have been avoided, if mask usage and social distancing were 20% more efficient, during the short period of the Delta and Omicron outbreak. Furthermore, the spread of the variants was assessed using viral load data. The data were recorded from PCR tests at 417 Army Equity Fund Hospital (NIMTS), in Athens and the Ct values from 746 patients with COVID-19 were processed, to explain transmission phenomena and disease severity in patients. The period when the Delta variant prevailed in the country, the average Ct value was calculated as 25.19 (range: 12.32-39.29), whereas during the period when the Omicron variant prevailed, the average Ct value was calculated as 28 (range: 14.41-39.36). In conclusion, our experimental study showed that the higher viral load, which is related to the Delta variant, may interpret the severity of the disease. However, no correlation was confirmed regarding contagiousness phenomena. The results of the model, Ct analysis and official data from NPHO are consistent.

Sequential viral introductions and spread of BA.1 across Pakistan provinces during the Omicron wave

BACKGROUND

COVID-19 waves caused by specific SARS-CoV-2 variants have occurred globally at different times. We focused on Omicron variants to understand the genomic diversity and phylogenetic relatedness of SARS-CoV-2 strains in various regions of Pakistan.

METHODS

We studied 276,525 COVID-19 cases and 1,031 genomes sequenced from December 2021 to August 2022. Sequences were analyzed and visualized using phylogenetic trees.

RESULTS

The highest case numbers and deaths were recorded in Sindh and Punjab, the most populous provinces in Pakistan. Omicron variants comprised 93% of all genomes, with BA.2 (32.6%) and BA.5 (38.4%) predominating. The first Omicron wave was associated with the sequential identification of BA.1 in Sindh, then Islamabad Capital Territory, Punjab, Khyber Pakhtunkhwa (KP), Azad Jammu Kashmir (AJK), Gilgit-Baltistan (GB) and Balochistan. Phylogenetic analysis revealed Sindh to be the source of BA.1 and BA.2 introductions into Punjab and Balochistan during early 2022. BA.4 was first introduced in AJK and BA.5 in Punjab. Most recent common ancestor (MRCA) analysis revealed relatedness between the earliest BA.1 genome from Sindh with Balochistan, AJK, Punjab and ICT, and that of first BA.1 from Punjab with strains from KPK and GB.

CONCLUSIONS

Phylogenetic analysis provides insights into the introduction and transmission dynamics of the Omicron variant in Pakistan, identifying Sindh as a hotspot for viral dissemination. Such data linked with public health efforts can help limit surges of new infections.

SARS-CoV-2 Next Generation Sequencing (NGS) data from clinical isolates from the East Texas Region of the United States

The SARS-CoV-2 virus has evolved throughout the pandemic and is likely to continue evolving into new variants. Some of these variants may affect functional properties, including infectivity, interactions with host immunity, and disease severity. And compromised vaccine efficacy is an emerging concern with every new viral variant. Next-generation sequencing (NGS) has emerged as the tool of choice for discovering new variants and understanding the transmission dynamics of SARS-CoV-2. Deciphering the SARS-CoV-2 genome has enabled epidemiological survivance and forecast of altered etiologically. Clinical presentations of the infection are influenced by comorbidities such as age, immune status, diabetes, and the infecting variant. Thus, clinical management and vaccine efficacy may differ for new variants. For example, some monoclonal antibody treatments are variant-specific, and some vaccines are less efficacious against the omicron and delta variants of SARS-CoV-2. Consequently, determining the local outbreaks and monitoring SARS-CoV-2 Variants of Concern (VOC) is one of the primary strategies for the pandemic's containment. Although next-generation sequencing (NGS) is a gold standard for genomic surveillance and variant discovery, the assays are not approved for variant diagnosis for clinical decision-making. Advanta Genetics, Texas, USA, optimized Illumina COVID-seq protocol to reduce cost without compromising accuracy and validated the Illumina COVID-Seq assay as a Laboratory Developed Test (LDT) according to the guidelines prescribed by the College of American Pathologists (CAP) and Clinical Laboratory Improvement Amendments (CLIA). The whole genome of the virus was sequenced in (n = 161) samples from the East Texas region using the Illumina MiniSeq® instrument and analyzed by using Illumina baseSpace (https://basespace.illumina.com) bioinformatics pipeline. Briefly, the library was prepared by using Illumina COVIDSeq research use only (RUO) kit, and the individual libraries were normalized using the DNA concentration measured by Qubit Flex Fluorometer, and the pooled libraries were sequenced on Illumina MiniSeq® Instrument. Illumina baseSpace application was used for sequencing QC, FASTQ generation, genome assembly, and identification of SARS-CoV-2 variants. This whole genome shotgun project (n = 161) has been deposited at GISAID.

Molecular epidemiology and transmission dynamics of multi-drug resistant tuberculosis strains using whole genome sequencing in the Amhara region, Ethiopia

BACKGROUND

Drug resistant Mycobacterium tuberculosis prevention and care is a major challenge in Ethiopia. The World health organization has designated Ethiopia as one of the 30 high burden multi-drug resistant tuberculosis (MDR-TB) countries. There is limited information regarding genetic diversity and transmission dynamics of MDR-TB in Ethiopia.

OBJECTIVE

To investigate the molecular epidemiology and transmission dynamics of MDR-TB strains using whole genome sequence (WGS) in the Amhara region.

METHODS

Forty-five MDR-TB clinical isolates from Amhara region were collected between 2016 and 2018, and characterized using WGS and 24-loci Mycobacterium Interspersed Repetitive Units Variable Number of Tandem Repeats (MIRU-VNTR) typing. Clusters were defined based on the maximum distance of 12 single nucleotide polymorphisms (SNPs) or alleles as the upper threshold of genomic relatedness. Five or less SNPs or alleles distance or identical 24-loci VNTR typing is denoted as surrogate marker for recent transmission.

RESULTS

Forty-one of the 45 isolates were analyzed by WGS and 44% (18/41) of the isolates were distributed into 4 clusters. Of the 41 MDR-TB isolates, 58.5% were classified as lineage 4, 36.5% lineage 3 and 5% lineage 1. Overall, TUR genotype (54%) was the predominant in MDR-TB strains. 41% (17/41) of the isolates were clustered into four WGS groups and the remaining isolates were unique strains. The predominant cluster (Cluster 1) was composed of nine isolates belonging to lineage 4 and of these, four isolates were in the recent transmission links.

CONCLUSIONS

Majority of MDR-TB strain cluster and predominance of TUR lineage in the Amhara region give rise to concerns for possible ongoing transmission. Efforts to strengthen TB laboratory to advance diagnosis, intensified active case finding, and expanded contact tracing activities are needed in order to improve rapid diagnosis and initiate early treatment. This would lead to the interruption of the transmission chain and stop the spread of MDR-TB in the Amhara region.

A Stochastic Mobility-Driven Spatially Explicit SEIQRD covid-19 Model with VOCs, Seasonality, and Vaccines

In this work, we extend our previously developed compartmental SEIQRD model for sars-cov-2 in Belgium. We introduce sars-cov-2 variants of concern, vaccines, and seasonality in our model, as their addition has proven necessary for modelling sars-cov-2 transmission dynamics during the 2020-2021 covid-19 pandemic in Belgium. The model is geographically stratified into eleven spatial patches (provinces), and a telecommunication dataset provided by Belgium's biggest operator is used to incorporate interprovincial mobility. We calibrate the model using the daily number of hospitalisations in each province and serological data. We find the model adequately describes these data, but the addition of interprovincial mobility was not necessary to obtain an accurate description of the 2020-2021 sars-cov-2 pandemic in Belgium. We further demonstrate how our model can be used to help policymakers decide on the optimal timing of the release of social restrictions.We find that adding spatial heterogeneity by geographically stratifying the model results in more uncertain model projections as compared to an equivalent nation-level model, which has both communicative advantages and disadvantages. We finally discuss the impact of imposing local mobility or social contact restrictions to contain an epidemic in a given province and find that lowering social contact is a more effective strategy than lowering mobility.

Coughs, colds and "freshers' flu" survey in the University of Cambridge, 2007-2008

Universities provide many opportunities for the spread of infectious respiratory illnesses. Students are brought together into close proximity from all across the world and interact with one another in their accommodation, through lectures and small group teaching and in social settings. The COVID-19 global pandemic has highlighted the need for sufficient data to help determine which of these factors are important for infectious disease transmission in universities and hence control university morbidity as well as community spillover. We describe the data from a previously unpublished self-reported university survey of coughs, colds and influenza-like symptoms collected in Cambridge, UK, during winter 2007-2008. The online survey collected information on symptoms and socio-demographic, academic and lifestyle factors. There were 1076 responses, 97% from University of Cambridge students (5.7% of the total university student population), 3% from staff and <1% from other participants, reporting onset of symptoms between September 2007 and March 2008. Undergraduates are seen to report symptoms earlier in the term than postgraduates; differences in reported date of symptoms are also seen between subjects and accommodation types, although these descriptive results could be confounded by survey biases. Despite the historical and exploratory nature of the study, this is one of few recent detailed datasets of influenza-like infection in a university context and is especially valuable to share now to improve understanding of potential transmission dynamics in universities during the current COVID-19 pandemic.

Factors driving norovirus transmission in long-term care facilities: A case-level analysis of 107 outbreaks

Norovirus is the most common cause of gastroenteritis outbreaks in long-term care facilities (LTCFs) in the United States, causing a high burden of disease in both residents and staff. Understanding how case symptoms and characteristics contribute to norovirus transmission can lead to more informed outbreak control measures in LTCFs. We examined line lists for 107 norovirus outbreaks that took place in LTCFs in five U.S. states from 2015 to 2019. We estimated the individual effective reproduction number, R_i, to quantify individual case infectiousness and examined the contribution of vomiting, diarrhea, and being a resident (vs. staff) to case infectiousness. The associations between case characteristics and R_i were estimated using a multivariable, log-linear mixed model with inverse variance weighting. We found that cases with vomiting infected 1.28 (95 % CI: 1.11, 1.48) times the number of secondary cases compared to cases without vomiting, and LTCF residents infected 1.31 (95 % CI: 1.15, 1.50) times the number of secondary cases compared to staff. There was no difference in infectiousness between cases with and without diarrhea (1.07; 95 % CI: 0.90, 1.29). This suggests that vomiting, particularly by LTCF residents, was a primary driver of norovirus transmission. These results support control measures that limit exposure to vomitus during norovirus outbreaks in LTCFs.

Optimization of the Illumina COVIDSeq™ protocol for decentralized, cost-effective genomic surveillance

A decentralized surveillance system to identify local outbreaks and monitor SARS-CoV-2 Variants of Concern is one of the primary strategies for the pandemic's containment. Although next-generation sequencing (NGS) is a gold standard for genomic surveillance and variant discovery, the technology is still cost-prohibitive for decentralized sequencing, particularly in small independent labs with limited resources. We have optimized the Illumina COVIDSeq™ protocol for the Illumina MiniSeq instrument to reduce cost without compromising accuracy. We slashed the library preparation cost by half by using 50% of recommended reagents at each step and normalizing the libraries before pooling to achieve uniform coverage. Reagent-only cost (∼$43.27/sample) for SARS-CoV-2 variant analysis with this normalized input protocol on MiniSeq instruments is comparable to what is achieved on high throughput instruments such as NextSeq and NovaSeq. Using this modified protocol, we tested 153 clinical samples, and 90% of genomic coverage was achieved for 142/153 samples analyzed in this study. The lineage was correctly assigned to all samples (152/153) except for one. This modified protocol can help laboratories with constrained resources to contribute in decentralized COVID-19 surveillance in the post-vaccination era.

Transmission Dynamics and Epidemiological Characteristics of the SARS-CoV-2 Delta Variant - Hunan Province, China, 2021

What is already known about this topic?

Little is known about the epidemiology, natural history, and transmission patterns of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant. Monitoring the evolution of viral fitness of SARS-CoV-2 in the host population is key for preparedness and response planning.

What is added by this report?

We analyzed a successfully contained local outbreak of Delta that took place in Hunan, China, and provided estimates of time-to-key event periods, infectiousness over time, and risk factors for SARS-CoV-2 infection and transmission for a still poorly understood variant.

What are the implications for public health practice?

Our findings simultaneously shed light on both the characteristics of the Delta variant, by identifying key age groups, risk factors, and transmission pathways, and planning a future response effort against SARS-CoV-2.

Coupling the Within-Host Process and Between-Host Transmission of COVID-19 Suggests Vaccination and School Closures are Critical

Most models of COVID-19 are implemented at a single micro or macro scale, ignoring the interplay between immune response, viral dynamics, individual infectiousness and epidemiological contact networks. Here we develop a data-driven model linking the within-host viral dynamics to the between-host transmission dynamics on a multilayer contact network to investigate the potential factors driving transmission dynamics and to inform how school closures and antiviral treatment can influence the epidemic. Using multi-source data, we initially determine the viral dynamics and estimate the relationship between viral load and infectiousness. Then, we embed the viral dynamics model into a four-layer contact network and formulate an agent-based model to simulate between-host transmission. The results illustrate that the heterogeneity of immune response between children and adults and between vaccinated and unvaccinated infections can produce different transmission patterns. We find that school closures play a significant effect on mitigating the pandemic as more adults get vaccinated and the virus mutates. If enough infected individuals are diagnosed by testing before symptom onset and then treated quickly, the transmission can be effectively curbed. Our multiscale model reveals the critical role played by younger individuals and antiviral treatment with testing in controlling the epidemic.

Resistance of Blastocystis to chlorine and hydrogen peroxide

Blastocystis is a ubiquitous, widely distributed protist inhabiting the gastrointestinal tract of humans and other animals. The organism is genetically diverse, and so far, at least 28 subtypes (STs) have been identified with ST1-ST9 being the most common in humans. The pathogenicity of Blastocystis is controversial. Several routes of transmission have been proposed including fecal-oral (e.g., zoonotic, anthroponotic) and waterborne. Research on the latter has gained traction in the last few years with the organism having been identified in various bodies of water, tap water, and rainwater collection containers including water that has been previously filtered and/or chlorinated. Herein, we assessed the resistance of 11 strains maintained in culture, spanning ST1-ST9 to various chlorine and hydrogen peroxide concentrations for 24 h, and performed recovery assays along with re-exposure. Following the treatment with both compounds, all subtypes showed increased resistance, and viability could be visualized at the cellular level. These results are hinting at the presence of mechanism of resistance to both chlorine and hydrogen peroxide. As such, this pilot study can be the platform for developing guidelines for water treatment processes.

Competitive evolution of H1N1 and H3N2 influenza viruses in the United States: A mathematical modeling study

Seasonal influenza causes vast public health and economic impact globally. The prevention and control of the annual epidemics remain a challenge due to the antigenic evolution of the viruses. Here, we presented a novel modeling framework based on changes in amino acid sequences and relevant epidemiological data to retrospectively investigate the competitive evolution and transmission of H1N1 and H3N2 influenza viruses in the United States during October 2002 and April 2019. To do so, we estimated the time-varying disease transmission rate from the reported influenza cases and the time-varying antigenic change rate of the viruses from the changes in amino acid sequences. By incorporating the time-varying antigenic change rate into the transmission models, we found that the models could capture the evolutionary transmission dynamics of influenza viruses in the United States. Our modeling results also showed that the antigenic change of the virus plays an essential role in seasonal influenza dynamics.

Epidemiological characteristics and transmission dynamics of the outbreak caused by the SARS-CoV-2 Omicron variant in Shanghai, China: A descriptive study

BACKGROUND

In early March 2022, a major outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant spread rapidly throughout Shanghai, China. Here we aimed to provide a description of the epidemiological characteristics and spatiotemporal transmission dynamics of the Omicron outbreak under the population-based screening and lockdown policies implemented in Shanghai.

METHODS

We extracted individual information on SARS-CoV-2 infections reported between January 1 and May 31, 2022, and on the timeline of the adopted non-pharmaceutical interventions. The epidemic was divided into three phases: i) sporadic infections (January 1-February 28), ii) local transmission (March 1-March 31), and iii) city-wide lockdown (April 1 to May 31). We described the epidemic spread during these three phases and the subdistrict-level spatiotemporal distribution of the infections. To evaluate the impact on the transmission of SARS-CoV-2 of the adopted targeted interventions in Phase 2 and city-wide lockdown in Phase 3, we estimated the dynamics of the net reproduction number (R_t ).

FINDINGS

A surge in imported infections in Phase 1 triggered cryptic local transmission of the Omicron variant in early March, resulting in the largest outbreak in mainland China since the original wave. A total of 626,000 SARS-CoV-2 infections were reported in 99.5% (215/216) of the subdistricts of Shanghai until the end of May. The spatial distribution of the infections was highly heterogeneous, with 37% of the subdistricts accounting for 80% of all infections. A clear trend from the city center towards adjacent suburban and rural areas was observed, with a progressive slowdown of the epidemic spread (from 463 to 244 meters/day) prior to the citywide lockdown. During Phase 2, R_t remained well above 1 despite the implementation of multiple targeted interventions. The citywide lockdown imposed on April 1 led to a marked decrease in transmission, bringing R_t below the epidemic threshold in the entire city on April 14 and ultimately leading to containment of the outbreak.

INTERPRETATION

Our results highlight the risk of widespread outbreaks in mainland China, particularly under the heightened pressure of imported infections. The targeted interventions adopted in March 2022 were not capable of halting transmission, and the implementation of a strict, prolonged city-wide lockdown was needed to successfully contain the outbreak, highlighting the challenges for containing Omicron outbreaks.

FUNDING

Key Program of the National Natural Science Foundation of China (82130093); Shanghai Rising-Star Program (22QA1402300).

Epidemiologic and import risk analysis of Peste des petits ruminants between 2010 and 2018 in India

BACKGROUND

Peste des petits ruminants (PPR) is a serious disease that affects goats, sheep and other small ruminants. As one of the earliest and most serious countries, PPR has seriously threatened India's animal husbandry economy.

RESULTS

In this study, the spatiotemporal characteristics of the PPR in India outbreaks were analyzed. Between 2010 and 2018, the epidemic in India broke out all over the country in a cluster distribution. Epidemic clusters in northern and southern India are at higher risk, and the outbreak time of PPR has significant seasonality. The results of the analysis of the development and transmission of PPR under the natural infection conditions showed that the PPR outbreak in India reached a peak within 15 days. Finally, the quantitative risk analysis results based on scenario tree show showed that the average probability of infecting PPRV in live sheep exported from India was 1.45 × 10^-4.

CONCLUSIONS

This study analyzed the prevalence of PPR in India. The analysis of transmission dynamics on the development of the epidemic provides a reference for the prevention and control of the epidemic. At the same time, it provides risk analysis and suggestions on trade measures for the trading countries of India.

Tick microbial associations at the crossroad of horizontal and vertical transmission pathways

BACKGROUND

Microbial communities can affect disease risk by interfering with the transmission or maintenance of pathogens in blood-feeding arthropods. Here, we investigated whether bacterial communities vary between Ixodes ricinus nymphs which were or were not infected with horizontally transmitted human pathogens.

METHODS

Ticks from eight forest sites were tested for the presence of Borrelia burgdorferi sensu lato, Babesia spp., Anaplasma phagocytophilum, and Neoehrlichia mikurensis by quantitative polymerase chain reaction (qPCR), and their microbiomes were determined by 16S rRNA amplicon sequencing. Tick bacterial communities clustered poorly by pathogen infection status but better by geography. As a second approach, we analysed variation in tick microorganism community structure (in terms of species co-infection) across space using hierarchical modelling of species communities. For that, we analysed almost 14,000 nymphs, which were tested for the presence of horizontally transmitted pathogens B. burgdorferi s.l., A. phagocytophilum, and N. mikurensis, and the vertically transmitted tick symbionts Rickettsia helvetica, Rickettsiella spp., Spiroplasma ixodetis, and Candidatus Midichloria mitochondrii.

RESULTS

With the exception of Rickettsiella spp., all microorganisms had either significant negative (R. helvetica and A. phagocytophilum) or positive (S. ixodetis, N. mikurensis, and B. burgdorferi s.l.) associations with M. mitochondrii. Two tick symbionts, R. helvetica and S. ixodetis, were negatively associated with each other. As expected, both B. burgdorferi s.l. and N. mikurensis had a significant positive association with each other and a negative association with A. phagocytophilum. Although these few specific associations do not appear to have a large effect on the entire microbiome composition, they can still be relevant for tick-borne pathogen dynamics.

CONCLUSIONS

Based on our results, we propose that M. mitochondrii alters the propensity of ticks to acquire or maintain horizontally acquired pathogens. The underlying mechanisms for some of these remarkable interactions are discussed herein and merit further investigation. Positive and negative associations between and within horizontally and vertically transmitted symbionts.

Transmission Dynamics and Effectiveness of Control Measures during COVID-19 Surge, Taiwan, April-August 2021

An unprecedented surge of COVID-19 cases in Taiwan in May 2021 led the government to implement strict nationwide control measures beginning May 15. During the surge, the government was able to bring the epidemic under control without a complete lockdown despite the cumulative case count reaching >14,400 and >780 deaths. We investigated the effectiveness of the public health and social measures instituted by the Taiwan government by quantifying the change in the effective reproduction number, which is a summary measure of the ability of the pathogen to spread through the population. The control measures that were instituted reduced the effective reproduction number from 2.0-3.3 to 0.6-0.7. This decrease was correlated with changes in mobility patterns in Taiwan, demonstrating that public compliance, active case finding, and contact tracing were effective measures in preventing further spread of the disease.

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.

The effects of COVID-19 transmission on environmental sustainability and human health: Paving the way to ensure its sustainable management

The transmission dynamics and health risks of coronavirus disease 2019 (COVID-19) pandemic are inextricably linked to ineract with environment, climate, air pollution, and meteorological conditions. The spread of COVID-19 infection can thus perturb the 'planetary health' and livelihood by exerting impacts on the temporal and spatial variabilities of environmental pollution. Prioritization of COVID-19 by the health-care sector has been posing a serious threat to economic progress while undermining the efforts to meet the United Nations' Sustainable Development Goals (SDGs) for environmental sustainability. Here, we review the multifaceted effects of COVID-19 with respect to environmental quality, climatic variables, SDGs, energy resilience, and sustainability programs. It is well perceived that COVID-19 may have long-lasting and profound effects on socio-economic systems, food security, livelihoods, and the 'nexus' indicators. To seek for the solution of these problems, consensus can be drawn to establish and ensure a sound health-care system, a sustainable environment, and a circular bioeconomy. A holistic analysis of COVID-19's effects on multiple sectors should help develop nature-based solutions, cleaner technologies, and green economic recovery plans to help maintain environmental sustainability, ecosystem resilience, and planetary health.

Quantitative microbial population study reveals geographical differences in bacterial symbionts of Ixodes ricinus

BACKGROUND

Ixodes ricinus ticks vector pathogens that cause serious health concerns. Like in other arthropods, the microbiome may affect the tick's biology, with consequences for pathogen transmission. Here, we explored the bacterial communities of I. ricinus across its developmental stages and six geographic locations by the 16S rRNA amplicon sequencing, combined with quantification of the bacterial load.

RESULTS

A wide range of bacterial loads was found. Accurate quantification of low microbial biomass samples permitted comparisons to high biomass samples, despite the presence of contaminating DNA. The bacterial communities of ticks were associated with geographical location rather than life stage, and differences in Rickettsia abundance determined this association. Subsequently, we explored the geographical distribution of four vertically transmitted symbionts identified in the microbiome analysis. For that, we screened 16,555 nymphs from 19 forest sites for R. helvetica, Rickettsiella spp., Midichloria mitochondrii, and Spiroplasma ixodetis. Also, the infection rates and distributions of these symbionts were compared to the horizontally transmitted pathogens Borrelia burgdorferi sensu lato, Anaplasma phagocytophilum, and Neoehrlichia mikurensis. The infection rates of all vertically transmitted symbionts differed between the study sites, and none of the symbionts was present in all tested ticks suggesting a facultative association with I. ricinus. The proportions in which symbionts occurred in populations of I. ricinus were highly variable, but geographically close study sites expressed similar proportions. These patterns were in contrast to what we observed for horizontally transmitted pathogens. Lastly, nearly 12% of tested nymphs were free of any targeted microorganisms, which is in line with the microbiome analyses.

CONCLUSIONS

Our results show that the microbiome of I. ricinus is highly variable, but changes gradually and ticks originating from geographically close forest sites express similar bacterial communities. This suggests that geography-related factors affect the infection rates of vertically transmitted symbionts in I. ricinus. Since some symbionts, such as R. helvetica can cause disease in humans, we propose that public health investigations consider geographical differences in its infection rates.

Estimating transmission dynamics of SARS-CoV-2 at different intraspatial levels in an institutional outbreak

Introduction

Large, localised outbreaks of COVID-19 have been repeatedly reported in high-density residential institutions. Understanding the transmission dynamics will inform outbreak response and the design of living environments that are more resilient to future outbreaks.

Methods

We developed an individual-based, multilevel transmission dynamics model using case, serology and symptom data from a 60-day cluster randomised trial of prophylaxes in a densely populated foreign worker dormitory in Singapore. Using Bayesian data augmentation, we estimated the basic reproduction number and the contribution that within-room, between-level and across-block transmission made to it, and the prevalence of infection over the study period across different spatial levels. We then simulated the impact of changing the building layouts in terms of floors and blocks on outbreak size.

Results

We found that the basic reproduction number was 2.76 averaged over the different putative prophylaxes, with substantial contributions due to transmission beyond the residents’ rooms. By the end of ~60 days of follow up, prevalence was 64.4 % (95 % credible interval 64.2–64.6 %). Future outbreak sizes could feasibly be halved by reducing the density to include additional housing blocks, or taller buildings, while retaining the overall number of men in the complex.

Discussion

The methods discussed can potentially be utilised to estimate transmission dynamics at any high-density accommodation site with the availability of case and serology data. The restructuring of infrastructure to reduce the number of residents per room can dramatically slow down epidemics, and therefore should be considered by policymakers as a long-term intervention.

Model-Based Projection of Zika Infection Risk with Temperature Effect: A Case Study in Southeast Asia

Zika virus (ZIKV) recently reemerged in the Americas and rapidly expanded in global range. It is posing significant concerns of public health due to its link to birth defects and its complicated transmission routes. Southeast Asia is badly hit by ZIKV, but limited information was found on the transmission potential of ZIKV in the region. In this paper, we develop a new dynamic process-based mathematical model, which incorporates the interactions among humans (sexual transmissibility), and between human and mosquitoes (biting transmissibility), as well as the essential impacts of temperature. The model is first validated by fitting the 2016 ZIKV outbreak in Singapore via Markov chain Monte Carlo method. Based on that, we demonstrate the effects of temperature on mosquito ecology and ZIKV transmission, and further clarify the potential risk of ZIKV outbreak in Southeast Asian countries. The results show that (i) the estimated infection reproduction number [Formula: see text] in Singapore fell from 6.93 (in which the contribution of sexual transmission was 0.89) to 0.24 after the deployment of control strategies; (ii) the optimal temperature for the reproduction of ZIKV infections and adult mosquitoes are estimated to be [Formula: see text]C and [Formula: see text]C, respectively; and (iii) the [Formula: see text] in Southeast Asia could be between 3 and 7, with an inverted-U shape around the year. The large values of [Formula: see text] and the simulative patterns of ZIKV transmission in each country highlights the high risk of ZIKV attack in Southeast Asia.

Transmission dynamics of COVID-19 in household and community settings in the United Kingdom, January to March 2020

BackgroundHouseholds appear to be the highest risk setting for COVID-19 transmission. Large household transmission studies in the early stages of the pandemic in Asia reported secondary attack rates ranging from 5 to 30%.AimWe aimed to investigate the transmission dynamics of COVID-19 in household and community settings in the UK.MethodsA prospective case-ascertained study design based on the World Health Organization FFX protocol was undertaken in the UK following the detection of the first case in late January 2020. Household contacts of cases were followed using enhanced surveillance forms to establish whether they developed symptoms of COVID-19, became confirmed cases and their outcomes. We estimated household secondary attack rates (SAR), serial intervals and individual and household basic reproduction numbers. The incubation period was estimated using known point source exposures that resulted in secondary cases.ResultsWe included 233 households with two or more people with 472 contacts. The overall household SAR was 37% (95% CI: 31-43%) with a mean serial interval of 4.67 days, an R₀ of 1.85 and a household reproduction number of 2.33. SAR were lower in larger households and highest when the primary case was younger than 18 years. We estimated a mean incubation period of around 4.5 days.ConclusionsRates of COVID-19 household transmission were high in the UK for ages above and under 18 years, emphasising the need for preventative measures in this setting. This study highlights the importance of the FFX protocol in providing early insights on transmission dynamics.

Transmission dynamics of COVID-19 in household and community settings in the United Kingdom, January to March 2020

BackgroundHouseholds appear to be the highest risk setting for COVID-19 transmission. Large household transmission studies in the early stages of the pandemic in Asia reported secondary attack rates ranging from 5 to 30%.AimWe aimed to investigate the transmission dynamics of COVID-19 in household and community settings in the UK.MethodsA prospective case-ascertained study design based on the World Health Organization FFX protocol was undertaken in the UK following the detection of the first case in late January 2020. Household contacts of cases were followed using enhanced surveillance forms to establish whether they developed symptoms of COVID-19, became confirmed cases and their outcomes. We estimated household secondary attack rates (SAR), serial intervals and individual and household basic reproduction numbers. The incubation period was estimated using known point source exposures that resulted in secondary cases.ResultsWe included 233 households with two or more people with 472 contacts. The overall household SAR was 37% (95% CI: 31-43%) with a mean serial interval of 4.67 days, an R0 of 1.85 and a household reproduction number of 2.33. SAR were lower in larger households and highest when the primary case was younger than 18 years. We estimated a mean incubation period of around 4.5 days.ConclusionsRates of COVID-19 household transmission were high in the UK for ages above and under 18 years, emphasising the need for preventative measures in this setting. This study highlights the importance of the FFX protocol in providing early insights on transmission dynamics.

Reconstructing the transmission dynamics of varicella in Japan: an elevation of age at infection

BACKGROUND

In Japan, routine two-dose immunization against varicella has been conducted among children at ages of 12 and 36 months since 2014, and the vaccination coverage has reached around 90%. To understand the impact of routine varicella vaccination, we reconstructed the epidemiological dynamics of varicella in Japan.

METHODS

Epidemiological and demographic datasets over the past three decades were analyzed to reconstruct the number of susceptible individuals by age and year. To estimate the annual risk of varicella infection, we fitted a balance equation model to the annual number of cases from 1990 to 2019. Using parameter estimates, we reconstructed varicella dynamics starting from 1990 and modeled future dynamics until 2033.

RESULTS

Overall varicella incidence declined over time and the annual risk of infection among children younger than 10 years old decreased monotonically starting in 2014. Conversely, varicella incidence among teenagers (age 10 to 14 years) has increased each year since 2014. A substantial number of unvaccinated individuals born before the routine immunization era remained susceptible and aged without contracting varicella, while the annual risk of infection among teenagers aged 10 to 14 years increased starting in 2011 despite gradual expansion of varicella vaccine coverage. The number of susceptible individuals decreased over time in all age groups. Modeling indicated that susceptibility rates among pre-school children aged 1 to 4 years will remain low.

CONCLUSION

Routine varicella vaccination has successfully reduced infections in pre-school and early primary school age children, but has also resulted in increased infection rates among adolescents. This temporary increase was caused both by the increased age of susceptible individuals and increased transmission risk among adolescents resulting from the dynamic nature of varicella transmission. Monitoring susceptibility among adolescents will be important to prevent outbreaks over the next decade.

Research on adaptive transmission and controls of COVID-19 on the basis of a complex network

COVID-19 has caused massive disruption on the global economy and presents a considerable risk to human lives. Some countries have successfully controlled the pandemic by adopting strict measures, such as lockdown and travel restriction, but such methods are difficult to be applied widely due to their huge costs. To explore available and low-cost solutions, this study proposes an adaptive transmission model on the basis of a complex network, and gives control simulation method of COVID-19. The suggested model considers adaptive changes such as travel network and people's travel intention to form a three-level adaptive network transmission model among cities, communities, and people. The improved susceptible-exposed-infectious-recovered-dead transmission process is integrated into the network. Simulation experiments under high-, low-, and conventional-cost controls are performed. In these experiments, the travel restriction and closing cities are considered, and sensitivity analyses of the parameters are conducted to explore low-cost measures. Meanwhile, time duration and application conditions of different controls are discussed. Results show that lockdown is the most effective way, and the contact and infection rates are the two most important factors to control the pandemic. Low-cost combined control measures are feasible and effective for most countries. Finally, several suggestions are given for national and urban preventions and controls of COVID-19 and other infectious diseases in the future.

Investigation and analysis on an outbreak of norovirus infection in a health school in Guangdong Province, China

Our objective was to describe the epidemiological features of an outbreak of norovirus infection in a health school in Guangdong province, China, to identify the cause of such a large scale outbreak of norovirus among older students, to simulate the transmission dynamics, and to evaluate the effect of intervention measures of GII.17 [P17] genotype norovirus infection. We identified all cases during the outbreak. Descriptive epidemiological, analytical epidemiological and hygiene survey methods were used to described the outbreak epidemic course and identify the cause of the outbreak of norovirus infection. We also used dynamical model to simulate the transmission dynamics of norovirus infection and evaluate the effect of intervention measures. Norovirus genotyping was assigned to the newly obtained strains, with a maximum likelihood phylogenetic analysis conducted. There were 360 cases of 42 classes in five grades with a 12.99% attack rate. Proportionally, more students were in contact with sick students and vomit in the suspected case group than the control group (χ² = 5.535, P = 0.019 and χ² = 5.549, P = 0.019, respectively). The basic reproduction number was 8.32 before and 0.49 after the intervention. Dynamical modeling showed that if the isolation rate was higher or case isolation began earlier, the total attack rate would decrease. Molecular characterization identified the GII.17 [P17] genotype in all stains obtained from the health school, which were clustered with high support in the phylogenetic tree. This was an outbreak of norovirus infection caused by contact transmission. The main reasons for the spread of the epidemic were the later control time, irregular treatment of vomit and no case isolation. The transmission dynamics of contact transmission was high, more efficient control measures should be employed.

The early phase of the COVID-19 epidemic in Lombardy, Italy

Background

In the night of February 20, 2020, the first epidemic of the novel coronavirus disease (COVID-19) outside Asia was uncovered by the identification of its first patient in Lombardy region, Italy. In the following weeks, Lombardy experienced a sudden increase in the number of ascertained infections and strict measures were imposed to contain the epidemic spread.

Methods

We analyzed official records of cases occurred in Lombardy to characterize the epidemiology of SARS-CoV-2 during the early phase of the outbreak. A line list of laboratory-confirmed cases was set up and later retrospectively consolidated, using standardized interviews to ascertained cases and their close contacts. We provide estimates of the serial interval, of the basic reproduction number, and of the temporal variation of the net reproduction number of SARS-CoV-2.

Results

Epidemiological investigations detected over 500 cases (median age: 69, IQR: 57–78) before the first COVID-19 diagnosed patient (February 20, 2020), and suggested that SARS-CoV-2 was already circulating in at least 222 out of 1506 (14.7%) municipalities with sustained transmission across all the Lombardy provinces. We estimated the mean serial interval to be 6.6 days (95% CrI, 0.7–19). Our estimates of the basic reproduction number range from 2.6 in Pavia (95% CI, 2.1–3.2) to 3.3 in Milan (95% CI, 2.9–3.8). A decreasing trend in the net reproduction number was observed following the detection of the first case.

Conclusions

At the time of first case notification, COVID-19 was already widespread in the entire Lombardy region. This may explain the large number of critical cases experienced by this region in a very short timeframe. The slight decrease of the reproduction number observed in the early days after February 20, 2020 might be due to increased population awareness and early interventions implemented before the regional lockdown imposed on March 8, 2020.

•

Over 500 cases (median age: 69, IQR: 57–78) declaring symptom onset before the notification of the first case (20 February 2020) were retrospectively detected.

•

SARS-CoV-2 was already circulating in at least 222 out of 1506 (14.7%) municipalities of Lombardy.

•

The estimated mean serial interval was 6.6 days (95% CrI, 0.7–19).

•

The basic reproduction number in the 12 provinces of Lombardy ranged from 2.6 (95% CI, 2.1–3.2) to 3.3 (95% CI, 2.9–3.8).

•

A decreasing trend in the net reproduction number following the detection of the epidemic and the introduction of the first restrictive measures.

Investigating the relationship between reopening the economy and implementing control measures during the COVID-19 pandemic

Objectives

The COVID-19 pandemic has resulted in an enormous burden on population health and the economy around the world. Although most cities in the United States have reopened their economies from previous lockdowns, it was not clear how the magnitude of different control measures—such as face mask use and social distancing—may affect the timing of reopening the economy for a local region. This study aimed to investigate the relationship between reopening dates and control measures and identify the conditions under which a city can be reopened safely.

Study design

This was a mathematical modeling study.

Methods

We developed a dynamic compartment model to capture the transmission dynamics of COVID-19 in New York City. We estimated model parameters from local COVID-19 data. We conducted three sets of policy simulations to investigate how different reopening dates and magnitudes of control measures would affect the COVID-19 epidemic.

Results

The model estimated that maintaining social contact at 80% of the prepandemic level and a 50% face mask usage would prevent a major surge of COVID-19 after reopening. If social distancing were completely relaxed after reopening, face mask usage would need to be maintained at nearly 80% to prevent a major surge.

Conclusions

Adherence to social distancing and increased face mask usage are keys to prevent a major surge after a city reopens its economy. The findings from our study can help policymakers identify the conditions under which a city can be reopened safely.

Duration of tick attachment necessary for transmission of Anaplasma phagocytophilum by Ixodes scapularis (Acari: Ixodidae) nymphs

This study assessed the duration of tick attachment necessary for a successful transmission of Anaplasma phagocytophilum by an infected I. scapularis nymph. Individual nymphs were placed upon BALB/c mice and allowed to feed for predetermined time intervals of 4 to 72 h. Ticks removed from mice at predetermined intervals were tested by PCR for verification of infection and evaluation of the bacterial load. The success of pathogen transmission to mice was assessed by blood-PCR at 7, 14 and 21 days postinfestation, and IFA at 21 days postinfestation. Anaplasma phagocytophilum infection was documented in 10-30 % of mice, from which ticks were removed within the first 20 h of feeding. However, transmission success was ≥70% if ticks remained attached for 36 h or longer. Notably, none of the PCR-positive mice that were exposed to infected ticks for 4 to 8 h and only half of PCR-positive mice exposed for 24 h developed antibodies within 3 weeks postinfestation. On the other hand, all mice with detectable bacteremia after being infested for 36 h seroconverted. This suggests that although some of the ticks removed prior to 24 h of attachment succeed in injecting a small amount of A. phagocytophilum, this amount is insufficient for stimulating humoral immunity and perhaps for establishing disseminated infection in BALB/c mice. Although A. phagocytophilum may be present in salivary glands of unfed I. scapularis nymphs, the amount of A. phagocytophilum initially contained in saliva appears insufficient to cause sustainable infection in a host. Replication and, maybe, reactivation of the agent for 12-24 h in a feeding tick is required before a mouse can be consistently infected.

Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in India

The novel SARS-CoV-2 virus, as it manifested in India in April 2020, showed marked heterogeneity in its transmission. Here, we used data collected from contact tracing during the lockdown in response to the first wave of COVID-19 in Punjab, a major state in India, to quantify this heterogeneity, and to examine implications for transmission dynamics. We found evidence of heterogeneity acting at multiple levels: in the number of potentially infectious contacts per index case, and in the per-contact risk of infection. Incorporating these findings in simple mathematical models of disease transmission reveals that these heterogeneities act in combination to strongly influence transmission dynamics. Standard approaches, such as representing heterogeneity through secondary case distributions, could be biased by neglecting these underlying interactions between heterogeneities. We discuss implications for policy, and for more efficient contact tracing in resource-constrained settings such as India. Our results highlight how contact tracing, an important public health measure, can also provide important insights into epidemic spread and control.

Transmission dynamics of SARS-CoV-2 in a mid-size city of China

BACKGROUND

An outbreak of pneumonia, COVID-19 associated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan city and then rapidly spread to other cities. Wenzhou is located approximately 900 km from Wuhan, which was experiencing an outbreak that was severe at the time but is considered modest as the epidemic became a pandemic. We described the epidemiological characteristics of SARS-CoV-2 outside of the epicenter to help understand the transmission pattern in a mid-sized Chinese city.

METHODS

To investigate the epidemiological and clinical characteristics of the COVID-19, we described case series of 473 patients with confirmed COVID-19 in Wenzhou, China from January 27 to March 16, 2020. We described the public health interventions of COVID-19 and evaluated the effect of interventions by the effective reproduction number (Rt).

RESULTS

The median age of all patients was 47.6 years, 48.4% of whom were female. 33.8% of the patients had a history of residence in Wuhan. Fever (71.7%) and cough (43.1%) were the most common symptoms. In addition, three kinds of unconventional cases were observed, namely 4.9% asymptomatic patients, 7.6% confirmed patients who had no link to Wuhan city but contact with individuals from Wuhan without any symptoms at the time of contact, and 12.9% confirmed patients who had an unknown source of transmission. We estimated that the basic reproductive number (R0) was 2.75 (95% CI: 2.37-3.23). The Rt fluctuated within the range of 2.50 to 3.74 from January 11 to January 16 while gradually reached a peak of 3.74 on January 16. Rt gradually decreased after January 16 and decreased to 1.00 on January 30. Rt continually decreased and reached the lowest point (0.03) on February 21, 2020.

CONCLUSION

Our study presented the possibility of asymptomatic carriers affected with SARS-CoV-2, and transmission by these three kinds of unconventional patients in Wenzhou may be an important characteristic of SARS-CoV-2 transmission. The evaluation showed that a series of multifaceted interventions proved effective in controlling the epidemic of COVID-19. These findings might provide valuable examples of control policies for countries or areas in combatting the global pandemic of COVID-19.

Infer HIV transmission dynamics from gene sequences among young men who have sex with men in China

To investigate the transmission dynamics and temporal and spatial migration characteristics of HIV spread among men who have sex with men (MSM) in China, a total of 1012 HIV-1 partial pol sequences, including five subtypes, were studied. Bayesian analysis were applied for each subtype to infer its dynamic characters including the effective reproductive number (R _e ) and migration process. The mean curve of each R _e was almost always greater than 1 (even the 95% highest posterior density (HPD) lower value) along with time, which supports the necessity for a comprehensive study about risk behaviors among young MSM group in China. We also should reappraise the free treatment strategy, especially the therapeutic effect during the free treatment policy.

Modeling and prediction of the transmission dynamics of COVID-19 based on the SINDy-LM method

The transmission dynamics of COVID-19 is investigated in this study. A SINDy-LM modeling method that can effectively balance model complexity and prediction accuracy is proposed based on data-driven technique. First, the Sparse Identification of Nonlinear Dynamical systems (SINDy) method is used to discover and describe the nonlinear functional relationship between the dynamic terms in the model in accordance with the observation data of the COVID-19 epidemic. Moreover, the Levenberg-Marquardt (LM) algorithm is utilized to optimize the obtained model for improving the accuracy of the SINDy algorithm. Second, the obtained model, which is consistent with the logistic model in mathematical form with small errors and high robustness, is leveraged to review the epidemic situation in China. Otherwise, the evolution of the epidemic in Australia and Egypt is predicted, which demonstrates that this method has universality for constructing the global COVID-19 model. The proposed model is also compared with the extreme learning machine (ELM), which shows that the prediction accuracy of the SINDy-LM method outperforms that of the ELM method and the generated model has higher sparsity.

Different intervention strategies toward live poultry markets against avian influenza A (H7N9) virus: Model-based assessment

BACKGROUND

Different interventions targeting live poultry markets (LPMs) are applied in China for controlling avian influenza A (H7N9), including LPM closure and "1110" policy (i.e., daily cleaning, weekly disinfection, monthly rest day, zero poultry stock overnight). However, the interventions' effectiveness has not been comprehensively assessed.

METHODS

Based on the available data (including reported cases, domestic poultry volume, and climate) collected in Guangdong Province between October 2013 and June 2017, we developed a new compartmental model that enabled us to infer H7N9 transmission dynamics. The model incorporated the intrinsic interplay among humans and poultry as well as the impacts of absolute humidity and LPM intervention, in which intervention strategies were parameterized and estimated by Markov chain Monte Carlo method.

RESULTS

There were 258 confirmed human H7N9 cases in Guangdong during the study period. If without interventions, the number would reach 646 (95%CI, 575-718) cases. Temporal, seasonal and permanent closures of LPMs can substantially reduce transmission risk, which might respectively reduce human infections by 67.2% (95%CI, 64.3%-70.1%), 75.6% (95%CI, 73.8%-77.5%), 86.6% (95%CI, 85.7-87.6%) in total four epidemic seasons, and 81.9% (95%CI, 78.7%-85.2%), 91.5% (95%CI, 89.9%-93.1%), 99.0% (95%CI, 98.7%-99.3%) in the last two epidemic seasons. Moreover, implementing the "1110" policy from 2014 to 2017 would reduce the cases by 34.1% (95%CI, 20.1%-48.0%), suggesting its limited role in preventing H7N9 transmission.

CONCLUSIONS

Our study quantified the effects of different interventions and execution time toward LPMs for controlling H7N9 transmission. The results highlighted the importance of closing LPMs during epidemic period, and supported permanent closure as a long-term plan.

Transmission dynamics of Staphylococcus aureus and Streptococcus agalactiae in a Dutch dairy herd using an automatic milking system

Staphylococcus aureus and Streptococcus agalactiae are important contagious mastitis pathogens and are considered to mainly transmit between cows through the milking machine. Controlling contagious mastitis on dairy farms requires a reduction of the transmission rate or the duration of intramammary infections (IMI), or both. These parameters may differ in dairy herds milked with an automatic milking system (AMS) as compared to those milked with a conventional milking system (CMS). The aims of this prospective longitudinal study were to estimate the transmission rate, the median duration of IMI and the basic reproduction number (R₀) of Staph. aureus and Strep. agalactiae in a Dutch AMS herd. Bacteriological cultures of quarter milk samples were collected every 2 wks. Using 3 different definitions of IMI, we estimated the transmission rate for Staph. aureus to be within the range of 0.002 (95 % CI: 0-0.005) quarter-day^-1 to 0.019 (95 % CI: 0.010-0.032) quarter-day^-1, and for Strep. agalactiae of 0.007 (95 % CI: 0.005-0.010) quarter-day^-1 to 0.019 (95 % CI: 0.011-0.032) quarter-day^-1, the median duration of chronic IMI at 95 (95 % CI: 72-125) days for Staph. aureus and at 86 (95 % CI: 67-111) days for Strep. agalactiae, and the R₀ between 0.16 (95 % CI: 0.05-0.27) and 0.34 (95 % CI: 0.20-0.48) for Staph. aureus, and between 0.64 (95 % CI: 0.41-0.87) and 0.68 (95 % CI: 0.48-0.88) for Strep. agalactiae. Transmission of these two contagious pathogens in this herd was limited and theoretically the IMI would not sustain, given that R₀ of both pathogens was lower than 1. The estimated transmission rate of Staph. aureus in this AMS herd was found to be comparable to those described for CMS herds, while for Strep. agalactiae, it was slightly higher than in CMS herds. The duration of Staph. aureus IMI was in line with results from CMS farms, while the duration of Strep. agalactiae was lower than what has been described in CMS herds. The R₀ of these contagious pathogens was found to be lower than the estimates in CMS herds. Our study suggests that the transmission rate of these two contagious pathogens in this AMS herd were comparable to what has been reported about well-performing CMS herds that have a low rate of transmission.

COVID-19 outbreak in Italy: estimation of reproduction numbers over 2 months prior to phase 2

Purpose

Two months after its first COVID-19 case, Italy counted more than 190,000 confirmed positive cases. From the beginning of April 2020, the nationwide lockdown started to show early effects by reducing the total cumulative incidence reached by the epidemic wave. Here we provide the reproduction number estimation both in space and in time from February 24 to April 24, 2020 over 2 months into the epidemic.

Methods

The aim of the present work was to provide a systematical mapping of the SARS-CoV-2 transmission dynamics spread to all regions of Italy. To do so, we estimated the basic reproduction number (R ₀ ), by using the maximum likelihood estimation method in the early stage of the epidemic. In addition, we determined time evolution of this parameter across the 2 months of the observational period. Finally, we linked R _t , with two indices, the first representing the number of contagious people and the latter the density of susceptibiltiy to infection of people in a region as recorded on April 24, 2020.

Results

Our estimates suggest a basic reproduction number averaged over all the regions of 3.29. Based on the SARS-CoV-2 transmission dynamics reported here, we gave a quantitative evaluation of the efficiency of the government measures to lower the reproduction number below 1 (control regime). We estimated that the worst-hit regions in Italy reached the control regime level (R _t  < 1) in about a month.

Conclusion

Our work was carried out in the period between April and July,2020. We found that the mean value of time to reach the control regime across the whole country was about 31 days from February 24, 2020. Moreover, we highlighted the interplay between the reproduction number and two epidemiological/demographic indices to evaluate the "state of activity" of the epidemic, potentially helping in challenging decisions to continue, ease, or tighten restrictions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10389-021-01567-1.

Transmission dynamics of novel Coronavirus-SARS-CoV-2 in South Sumatera, Indonesia

SARS-CoV-2 has shaken the world by extremely raising death tolls, illnesses, and economic losses. The virus is transmitted by humans to other humans, spreading to more than 200 countries. This research aims to analyze the transmission dynamics of novel Coronavirus-SARS-CoV-2 in South Sumatera Indonesia. This is epidemiologic research, and the research population is all SARS-CoV-2 patients and those who have close contact with the patients in all districts/cities in South Sumatera. It has been widely known that those that have made contact with patients confirmed positive for SARS-CoV-2 has a risk of getting infected by SARS-CoV-2 by 3.591 higher than those who never have (OR = 3.591, 95% CI: 2.933-4.396). Also, according to the findings, those who have a contact history to patients confirmed positive for SARS-CoV-2 have a risk of getting infected by SARS-CoV-2 by 2.387 higher than those who never have (OR = 2.387, 95% CI: 1.362-4.184). Meanwhile, those who have no idea for having made contact with patients confirmed positive for SARS-CoV-2 has a risk of getting infected by SARS-CoV-2 by 1.082 higher than those who have never a contact history to the SARS-CoV-2 patients (OR = 1.082, 95% CI: 0.622-1.882). To prevent broader transmission, those who have made contact with the SARS-CoV-2 patients need to be quarantined. The findings help us give community health interventions to globally fight this transmittable disease.