Outbreak Stages Research Articles

Modelling plausible scenarios for the Omicron SARS-CoV-2 variant from early-stage surveillance

We used a spatially explicit agent-based model of SARS-CoV-2 transmission combined with spatially fine-grained COVID-19 observation data from Public Health Scotland to investigate the initial rise of the Omicron (BA.1) variant of concern. We evaluated plausible scenarios for transmission rate advantage and vaccine immune escape relative to the Delta variant based on the data that would have been available at that time. We also explored possible outcomes of different levels of imposed non-pharmaceutical intervention. The initial results of these scenarios were used to inform the Scottish Government in the early outbreak stages of the Omicron variant.Using the model with parameters fit over the Delta variant epidemic, some initial assumptions about Omicron transmission rate advantage and vaccine escape, and a simple growth rate fitting procedure, we were able to capture the initial outbreak dynamics for Omicron. We found that the modelled dynamics hold up to retrospective scrutiny. The modelled imposition of extra non-pharmaceutical interventions planned by the Scottish Government at the time would likely have little effect in light of the transmission rate advantage held by the Omicron variant and the fact that the planned interventions would have occurred too late in the outbreak’s trajectory. Finally, we found that any assumptions made about the projected distribution of vaccines in the model population had little bearing on the outcome, in terms of outbreak size and timing. Instead, it was the landscape of prior immunity that was most important.

Delineation of outbreak stages of the coral-killing sponge Terpios hoshinota

Outbreaks of the cyanobacteriosponge Terpios hoshinota are one of the many issues contributing to coral reef decline in the Indo-Pacific. This species occasionally undergoes local outbreaks, becoming an aggressive space competitor and overgrowing and killing zooxanthellate corals. Large outbreaks have been observed in Taiwan and the Ryukyu Islands in southern Japan. Many questions regarding the characteristics and chronology of T. hoshinota outbreaks remain unsolved. Therefore, the aim of this research was to identify outbreak stages at an outbreak site (Ogimi) on the west coast of northern Okinawa Island, Japan. We developed a novel approach to understand the chronology of outbreaks. Distinct outbreak stages were defined based on observations, in which Terpios: 1) starts overgrowing coral colonies, 2) covers a whole coral colony, 3) in the case of branching corals, causes the coral colony to collapse, and 4) the sponge is eventually overgrown by other organisms including turf algae and other sponges. Analyses were done based on photographic transects and the relative proportions of each stage were calculated. Results showed Ogimi is likely in final outbreak stages as overgrown Terpios had the highest share of all stages (57.9% and 44.9% at two outbreak sites), while smaller patches of Terpios, marking the starting point of the successional process, made up less than 1.5% of all observations. We suggest collecting such stage information during Terpios monitoring as it can allow identification of outbreaks at early stages, and potentially identify global patterns.

Long-Term Spatiotemporal Characteristics of Ulva prolifera Green Tide and Effects of Environmental Drivers on Its Monitoring by Satellites: A Case Study in the Yellow Sea, China, from 2008 to 2023

Ulva prolifera (U. prolifera) green tide outbreaks have occurred in the Yellow Sea of China for many years, causing serious losses to marine ecology and the marine economy. The monitoring and tracking of U. prolifera green tide is a crucial aspect of marine ecological disaster prevention and control management. This paper aims to investigate the spatiotemporal distribution changes in U. prolifera green tide in the Yellow Sea throughout its life cycle. A survey of the Yellow Sea from 2008 to 2023 was conducted using multi-source remote sensing images. Long-term monitoring and analysis of U. prolifera revealed the evolution process of the green tide, including the early development, outbreak, decline, and extinction stages, considering time, space, and frequency of occurrence. Additionally, this study examined peak coverage change patterns over the past 16 years and analyzed the influence of environmental factors such as sea surface temperature and sea surface wind field on the development of U. prolifera. The research results serve as a valuable reference for the monitoring, early warning, and scientific prevention and control of U. prolifera green tide in the Yellow Sea, as well as other similar marine disaster areas.

Cyanobacterial blooms control with CaO2 in different stages: Inhibition efficiency, water quality optimization and microbial community changes

This study explored the feasibility of calcium peroxide (CaO2) to inhibit cyanobacterial blooms of the outbreak and dormancy stages. Our previous studies have found that CaO2 has a high inhibitory effect on cyanobacteria. In order to explore the application effect of CaO2 in actual cyanobacteria lake water, we conducted this study to clarify the effect of CaO2 on inhibiting cyanobacteria in outbreak and dormancy stages. The results showed that CaO2 inhibited the growth of cyanobacteria in the outbreak and dormancy stages by 98.7% and 97.6%, respectively. The main inhibitory mechanism is: (1) destroy the cell structure and make the cells undergo programmed cell death by stimulating the oxidation balance of cyanobacteria cells; (2) EPS released by cyanobacteria resist stimulation and combine calcium to form colonies, and accelerate cell settlement. In addition to causing direct damage to cyanobacteria, CaO2 can also improve water quality and sediment microbial diversity, and reduce the release of sediment to phosphorus, so as to further contribute to cyanobacterial inhibition. Finally, the results of qRT-PCR analysis confirmed the promoting effect of CaO2 on the downregulation of photosynthesis-related genes (rbcL and psaB), microcystn (mcyA and mcyD) and peroxiredoxin (prx), and verified the mechanism of CaO2 inhibition of cyanobacteria. In conclusion, this study provides new findings for the future suppression of cyanobacterial bloom, by combining water quality, cyanobacterial inhibition mechanisms, and sediment microbial diversity.

Netizens' concerns during COVID-19: a topic evolution analysis of Chinese social media platforms

PurposeThis study analyzes the evolution of topics related to COVID-19 on Chinese social media platforms with the aim of identifying changes in netizens' concerns during the different stages of the pandemic.Design/methodology/approachIn total, 793,947 posts were collected from Zhihu, a Chinese Question and Answer website, and Dingxiangyuan, a Chinese online healthcare community, from 31 December, 2019, to 4 August, 2021. Topics were extracted during the prodromal and outbreak stages, and in the abatement–resurgence cycle.FindingsNetizens' concerns varied in different stages. During the prodromal and outbreak stages, netizens showed greater concern about COVID-19 news, the impact of COVID-19 and the prevention and control of COVID-19. During the first round of the abatement and resurgence stage, netizens remained concerned about COVID-19 news and the prevention and control of the pandemic, however, less attention was paid to the impact of COVID-19. During later stages, popularity grew in topics concerning the impact of COVID-19, while netizens engaged more in discussions about international events and the raising of spirits to fight the global pandemic.Practical implicationsThis study contributes to the practice by providing a way for the government and policy makers to retrospect the pandemic and thereby make a good preparation to take proper measures to communicate with citizens and address their demands in similar situations in the future.Originality/valueThis study contributes to the literature by applying an adapted version of Fink's (1986) crisis life cycle to create a five-stage evolution model to understand the repeated resurgence of COVID-19 in Mainland China.

Understanding bike-sharing mobility patterns in response to the COVID-19 pandemic

The COVID-19 pandemic lasting for several years brings huge challenges to the bike-sharing system and even society structure. It is urgent to explore the pandemic impacts on mobility patterns through outbreak and recovery stages from network perspective. This paper proposed a comprehensive approach to investigate the bike-sharing mobility patterns with the case in Washington D.C., which is also new perspective for human mobility patterns. Multiple-source data, including bike-sharing trip information, COVID-19 information, geographic and POI information, were collected. Although the total bike-sharing trips decreased significantly in spatial-temporal analysis, the trips made by casual users gradually increased through outbreak and recovery of pandemic, indicating the change of travel habits. In addition, the docking stations and trips from 2019 to 2022 were utilized to construct the bike-sharing network. The results present that major network properties, such as connectivity, clustering coefficient, and accessibility, experienced significant decrease in 2020 and strong recovery in 2021 and 2022, which demonstrated the well resilience of bike-sharing system. Moreover, through the detection of community with modularity method, the evolution of community structure in response to the outbreak and recovery of pandemic was captured. Although the travel distance and time for bike-sharing trips changed from 2019 to 2022, the basic three community layout are still stable. To better understand the community structure, the POI (Point of Interests) auxiliary analysis was conducted and central community was found to have similar proportion of POIs even during the pandemic. These results provide references for bike-sharing management and operation policy through outbreak and recovery of pandemic.

Direct indicators of social distancing effectiveness in COVID-19 outbreak stages: a correlational analysis of case contacts and population mobility in Korea.

The effectiveness of social distancing during the coronavirus disease 2019 (COVID-19) pandemic has been evaluated using the magnitude of changes in population mobility. This study aimed to investigate a direct indicator-namely, the number of close contacts per patient with confirmed COVID-19. From week 7, 2020 to week 43, 2021, population movement changes were calculated from the data of two Korean telecommunication companies and Google in accordance with social distancing stringency levels. Data on confirmed cases and their close contacts among residents of Gyeonggi Province, Korea were combined at each stage. Pearson correlation analysis was conducted to compare the movement data with the change in the number of contacts for each confirmed case calculated by stratification according to age group. The reference value of the population movement data was set using the value before mid-February 2020, considering each data's characteristics. In the age group of 18 or younger, the number of close contacts per confirmed case decreased or increased when the stringency level was strengthened or relaxed, respectively. In adults, the correlation was relatively low, with no correlation between the change in the number of close contacts per confirmed case and the change in population movement after the commencement of vaccination for adults. The effectiveness of governmental social distancing policies against COVID-19 can be evaluated using the number of close contacts per confirmed case as a direct indicator, especially for each age group. Such an analysis can facilitate policy changes for specific groups.

P150 Psychological distress during hospitalization for breast cancer patients in the outbreak, post-peak, and normalization stages of the COVID-19 pandemic

P150 Psychological distress during hospitalization for breast cancer patients in the outbreak, post-peak, and normalization stages of the COVID-19 pandemic

Phytolith Content Negatively Affects Forage Quality of Eragrostis curvula (Schrad.) Nees

Phytoliths are intra and extracellular siliceous deposits present in different plant tissues. Si uptake and transport are mediated by Lsi genes and its concentration is associated with forage quality. Our objective was to determine the phytolith content in seven Eragrostis curvula genotypes at the outbreak and re-growth stages to assess its relationship with the forage quality parameters and perform a genome-wide analysis to detect the presence/absence of Lsi genes. The mean values of the phytolith content of dry matter varied between 1.94–2.26% and 2.72–4.71% at the outbreak and re-growth stages, respectively, with highly significant differences among the genotypes and phenological stages. A highly negative correlation was observed in the phytolith content and in vitro dry matter digestibility and crude protein, revealing its importance as a selection parameter in breeding programs. A positive correlation was obtained between the phytolith content and lignin, neutral detergent fiber, and acid detergent fiber. The main morphotypes of the phytoliths included saddle-shaped, bulliform, and acicular cells. Genes Lsi1, Lsi2, Lsi3, and Lsi6, previously reported in silica uptake, were identified and compared with related species, being the gene sequences highly conserved, meaning that its accumulation is probably due to differences in the gene expression or different allelic variants among cultivars.

Quantitative discrimination of algae multi-impacts on N2O emissions in eutrophic lakes: Implications for N2O budgets and mitigation

It is generally accepted that eutrophic lakes significantly contribute to nitrous oxide (N2O) emissions. However, how these emissions are affected by the formation, disappearance, and mechanisms of algal blooms in these lakes has not been systematically investigated. This study examined and determined the relative contribution of spatiotemporal N2O production pathways in hypereutrophic Lake Taihu. Synchronously, the multi-impacts of algae on N2O production and release potential were measured in the field and in microcosms using isotope ratios of oxygen (δ18O) and bulk nitrogen (δ15N) to N2O and to intramolecular 15N site preference (SP). Results showed that N2O production in Lake Taihu was derived from microbial effects (nitrification and incomplete denitrification) and water air exchanges. N2O production was also affected by the N2O reduction process. The mean dissolved N2O concentrations in the water column during the pre-outbreak, outbreak, and decay stages of algae accumulation were almost the same (0.05 μmol·L–1), which was 2–10 times higher than in lake areas algae was not accumulating. However, except for the central lake area, all surveyed areas (with and without accumulated algae) displayed strong release potential and acted as the emission source because of dissolved N2O supersaturation in the water column. The mean N2O release fluxes during the pre-outbreak, outbreak, and decay stages of algae accumulation areas were 17.95, 26.36, and 79.32 μmol·m–2·d–1, respectively, which were 2.0–7.5 times higher than the values in the non-algae accumulation areas. In addition, the decay and decomposition of algae released large amounts of nutrients and changed the physiochemical properties of the water column. Additionally, the increased algae biomass promoted N2O release and improved the proportion of N2O produced via denitrification process to being 9.8–20.4% microbial-derived N2O. This proportion became higher when the N2O consumption during denitrification was considered as evidenced by isotopic data. However, when the algae biomass was excessive in hypereutrophic state, the algae decomposition also consumed a large amount of oxygen, thus limiting the N2O production due to complete denitrification as well as due to the limited substrate supply of nitrate by nitrification in hypoxic or anoxic conditions. Further, the excessive algae accumulation on the water surface reduced N2O release fluxes via hindering the migration of the dissolved N2O into the atmosphere. These findings provide a new perspective and understanding for accurately evaluating N2O release fluxes driven by algae processes in eutrophic lakes.

Impact of random and targeted disruptions on information diffusion during outbreaks

Outbreaks are complex multi-scale processes that are impacted not only by cellular dynamics and the ability of pathogens to effectively reproduce and spread, but also by population-level dynamics and the effectiveness of mitigation measures. A timely exchange of information related to the spread of novel pathogens, stay-at-home orders, and other measures can be effective at containing an infectious disease, particularly during the early stages when testing infrastructure, vaccines, and other medical interventions may not be available at scale. Using a multiplex epidemic model that consists of an information layer (modeling information exchange between individuals) and a spatially embedded epidemic layer (representing a human contact network), we study how random and targeted disruptions in the information layer (e.g., errors and intentional attacks on communication infrastructure) impact the total proportion of infections, peak prevalence (i.e., the maximum proportion of infections), and the time to reach peak prevalence. We calibrate our model to the early outbreak stages of the SARS-CoV-2 pandemic in 2020. Mitigation campaigns can still be effective under random disruptions, such as failure of information channels between a few individuals. However, targeted disruptions or sabotage of hub nodes that exchange information with a large number of individuals can abruptly change outbreak characteristics, such as the time to reach the peak of infection. Our results emphasize the importance of the availability of a robust communication infrastructure during an outbreak that can withstand both random and targeted disruptions.

URBAN FORM AND SPATIOTEMPORAL VULNERABILITY OF LOCAL COMMUNITIES TO COVID-19

ABSTRACT This paper investigates spatiotemporal dynamics of the effects of urban form on the Covid-19 spread within local communities in Salt Lake County, Utah, in the United States. We identify three types of communities—minority, traditional urban and suburban, and new suburban—and three stages throughout March 2020—September 2021, reflecting the initial, outbreak, and recovery stages. While the traditional urban and suburban communities experience the least risk of Covid-19, minority communities are severely impacted in the initial and outbreak stages, and remote suburban communities are primarily affected in the outbreak and recovery stages. The regression further reveals the role of urban form in the pandemic. High-density urban land use is the main density factor contributing to the disease’s spread. In the initial stage, mobility factors such as street connectivity and walkability contribute to the local spread, while land use mixture is the catalyst in the outbreak stage. A comprehensive compact development might offset these negative effects on local public health, and its contribution to local resilience in the recovery stage is also confirmed. Thus, compact development is still valuable for building urban resilience, and proper planning and policies can offset the potential adverse effects of pandemics.

Use of nanoparticle biosensors to evaluate carnivore health: A new approach

The canine distemper virus (CDV) causes a common fatal disease in carnivores that has led to the local extinction of some species. Timely and effective monitoring and diagnosis of the spread of CDV are essential because these can contribute to containing and planning control strategies in early outbreak stages. The use of nanoparticle-based biosensors (NPs) is a novel alternative. A systematic analysis of NP design, use, and scope provides a clue on the potential application of this technology in CDV diagnosis and control. In this sense, the present paper outlines the most recent findings on the use of biosensors to diagnose canine distemper. We conducted a literature review of the use of biosensors to diagnose different viruses of human and zoonotic importance. Biosensors designed for the diagnosis and control of CDV were then searched and analyzed. Searches were conducted in scientific databases with the keywords "Canine Distemper Virus”, “nanoparticles”, and “biosensors”. No studies on wildlife were found. We found 50 studies addressing the development and application of virus biosensors in domestic animals and under laboratory conditions. The use of metallic NPs with optical properties — for example, gold NPs and quantum dots — have been the main systems for the design of biosensors used in CDV diagnosis and control. Future steps include the application of this technology in widely distributed wildlife species, e. g., coyote, by developing a device with a CDV-specific biosensor for in-situ detection, avoiding the need to capture individuals. Detecting CDV-infected populations in real-time will improve the management and containment of the disease to preserve the health of ecosystems.

The ecological responses of bacterioplankton during a Phaeocystis globosa bloom in Beibu Gulf, China highlighted by integrated metagenomics and metatranscriptomics

The interaction between bacteria and phytoplankton during bloom events is complicated throughout the developmental processes of algal blooms. The detailed ecological roles of bacterioplankton during algal blooms still need to be investigated comprehensively. With the assistance of omics techniques, the composition and function of bacterioplankton were studied during the blooming and recession periods of Phaeocystis globosa in the Beibu Gulf, China. The transcriptionally active taxa of Vibrio, which correlated with most functional genes, were enriched in the blooming period, whereas the active microbial groups, such as Erythrobacter and Candidatus puniceispirillum, increased significantly in the recession period of the P. globosa bloom. The transcriptional analyses indicated the blooming and recession periods of P. globosa had different impacts on the function of bacterioplankton, including shifts in expression of specific metabolic pathways for variable nutritional utilization and their advantage in bacterial motility, quorum sensing, and extracellular secretion. Overall, the integrated field investigation and in-depth analysis of molecular data highlighted the difference of bacterial community during the outbreak and collapse stages of P. globosa bloom, and provided fundamental data for better understanding of the bacterial community in response to blooming and recession of the P. globosa bloom.

Complex network-based research on organization collaboration and cooperation governance responding to COVID-19

PurposeWith multiple-related organizations, worldwide infections, deep economic recession and public disorder, and large consumption amount of anti-epidemic resources, the coronavirus disease 2019 (COVID-19) has been defined as a public health emergency of international concern (PHEIC). Nowadays, Wuhan has recovered from the pandemic disaster and reentered normalization. The purposes of this study are to (1) summarize organization collaboration patterns, successful experience and latent defects under across-stage evolution of Wuhan's cooperation governance mode against the pandemic, and on the basis, (2) reveal how the COVID-19 development trends and organizations' collaborative behaviors affected each other.Design/methodology/approachDetailed content analysis of online news reports covering COVID-19 prevention and control measures on the website of Wuhan Municipal Government was adopted to identify organizations and their mutual collaborative interrelationships. Four complex network (CN) models of organization collaboration representing the outbreak, preliminary control, recession and normalization stages, respectively, were established then. Time-span-based dynamic parameter analyses of the proposed networks, comprising network cohesiveness analysis and node centrality analysis, were undertaken to indicate changes of global and local characteristics in networks.FindingsFirst, the definite collaborative status of Wuhan Headquarters for Pandemic Prevention and Control (WHPPC) has persisted throughout the period. Medical institutions and some other administrations were the most crucial participants collaborating with the WHPPC. Construction-industry organizations altered pandemic development trends twice to make the situation controllable. Media, large-scale enterprises, etc. set about underscoring themselves contributions since the third stage. Grassroots cadres and healthcare force, small and medium-sized enterprises (SMEs), financial institutions, etc. were essential collaborated objects. Second, four evolution mechanisms of organization collaboration responding to the COVID-19 in Wuhan has been proposed.Research limitations/implicationsFirst, universality of Wuhan-style governance experience may be affected. Second, the stage-dividing process may not be the most appropriate. Then, data source was single and link characteristics were not considered when modeling.Practical implicationsThis study may offer beneficial action guidelines to governmental agencies, the society force, media, construction-industry organizations and the market in other countries or regions suffering from COVID-19. Other organizations involved could also learn from the concluded organizations' contributions and four evolution mechanisms to find improvement directions.Originality/valueThis study adds to the current theoretical knowledge body by verifying the feasibility and effectiveness of investigating cooperation governance in public emergencies from the perspectives of analyzing the across-stage organization collaboration CNs.

Pattern of Time-to-Surgery in Patients With Breast Cancer at Different Stages of the COVID-19 Pandemic.

BackgroundThe management of cancer surgeries is under unprecedented challenges during the COVID-19 pandemic, and the breast cancer patients may face a time-delay in the treatment. This retrospective study aimed to present the pattern of time-to-surgery (TTS) and analyze the features of breast cancer patients under the different stages of the COVID-19 pandemic.MethodsPatients who received surgeries for breast cancers at West China Hospital between February 15, 2020 and April 30, 2020 (the outbreak and post-peak stages), and between March 10, 2021 and May 25, 2021 (the normalization stage) were included. TTS was calculated as the time interval between the pathological diagnosis and surgical treatment of breast cancer patients. And the pandemic was divided into three stages based on the time when the patients were pathologically diagnosed and the severity of pandemic at that time point. TTS, demographic and clinicopathological features were collected from medical records.ResultsA total of 367 patients were included. As for demographic features, it demonstrated statistically significant differences in insurance type (p<0.001) and regular screening (p<0.001), as well as age (p=0.013) and menstrual status (p=0.004). As for clinicopathological features, axillary involvement (p=0.019) was a factor that differed among three stages. The overall TTS was 23.56 ± 21.39 days. TTS for patients who were diagnosed during the outbreak of COVID-19 were longer than those diagnosed during pandemic post-peak and normalization stage (p<0.001). Pandemic stage (p<0.001) and excision biopsy before surgery (OR, 6.459; 95% CI, 2.225-18.755; p=0.001) were markedly correlated with the TTS of patients.ConclusionsTTS of breast cancer patients significantly varied in different stages of the COVID-19 pandemic. And breast cancer patients’ daily lives and disease treatments were affected by the pandemic in many aspects, such as health insurance access, physical screening and change of therapeutic schedules. As the time-delay may cause negative influences on patients’ disease, we should minimize the occurrence of such time-delay. It is vital to come up with comprehensive measures to deal with unexpected situations in case the pandemic occurs.

Characteristics of post-Wuhan COVID-19 outbreaks in mainland China

Objective: To review the characteristic of Coronavirus disease 2019 (COVID-19) outbreaks in mainland China, particularly post-Wuhan outbreaks, and to help design effective responses in the foreseeable future. Method: The data regarding COVID-19 outbreaks between December 2019 and March 16, 2022 were obtained from China's publicly available databases. The data were analyzed using descriptive statistics. Five outbreak stages were defined according to distinct epidemiological characteristics across different time periods over the past two years. Result: Since the 2020 Wuhan outbreak, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) local infections were confirmed in 37 995 cases as of March 16, 2022. We identified 285 isolated outbreaks in unrelated people that occurred in four additional distinct stages, over 57% of which had been imported, such as imported infected travelers and fomite transmission. The basic reproduction number (R0) of original SARS-CoV-2 was about 2.79, while the Delta variant was about 5.08 and Omicron was 7.0 or greater, resulting in the disease being more contagious during the fourth (Delta) and fifth (Omicron) stages than previous stages. Conclusion: China has experienced various COVID-19 outbreaks of different levels since the start of the pandemic in Wuhan, and local transmission is mainly caused by imported sources. If the “dynamic COVID-zero” policy is not appropriately followed, it will be difficult to contain the spread in China from overseas and to cope with the Omicron variant.

Effects of cyanobacterial growth and decline on the &lt;i&gt;phoD&lt;/i&gt;-harboring bacterial community structure in sediments of Lake Chaohu

phoD基因编码的碱性磷酸酶驱动沉积物有机磷矿化并释放生物可利用磷，促进了富营养化湖泊蓝藻的生长与暴发，但对富营养化湖泊蓝藻生消周期phoD基因细菌群落动态变化的认识依然有限.本文研究了中国典型富营养化湖泊巢湖蓝藻生消过程沉积物碱性磷酸酶活性（APA）、phoD基因细菌多样性和群落结构的动态变化及其与环境的关系.结果显示：巢湖沉积物APA活性在蓝藻生长与暴发阶段显著升高，且与水温、pH、溶解氧（DO）等环境因子显著相关.蓝藻生消各阶段沉积物phoD基因细菌群落的优势菌属均由Pseudonocardia和Friedmanniella构成；与蓝藻潜伏期和衰亡期相比，生长初期与暴发期大多数样点沉积物Pseudonocardia的丰度显著降低而Friedmanniella显著升高.携带phoD基因的菌属丰度呈显著的时空变化，其中菌属丰度的空间异质性较高.蓝藻生长初期与暴发期的phoD基因细菌群落的Ace指数与Shannon多样性指数显著大于潜伏期与衰亡期.研究表明，携带phoD基因细菌群落结构的变化主要受APA、DO、叶绿素a、水温、总磷以及无机磷的驱动；春季蓝藻的生长消耗大量上覆水溶解性无机磷，激发了沉积物APA活性并诱发Friedmanniella生长从而缓解水体磷限制.;The alkaline phosphatase encoded by phoD gene drives the mineralization of organic phosphorus in sediments and thus the release of bioavailable phosphorus, and promotes the growth and blooms of cyanobacteria in eutrophic lakes. The dynamic variations of phoD-harboring bacterial community during the annual cyanobacterial growth and decline in eutrophic lakes, however, remain unclear. In this study, we analyzed the alkaline phosphatase activity (APA), phoD-harboring bacterial community diversity and structure and their associations with the physicochemical factors in a typical eutrophic lake (Lake Chaohu) in China during the entire cyanobacterial growth and decline. The results showed that the APA in sediments increased significantly during the initial growth and outbreaks of cyanobacteria. Pseudonocardia and Friedmanniella are the predominant phoD-harboring genera in sediments during the entire cyanobacterial growth and decline. In contrast to the abundance of Pseudonocardia and Friedmanniella in the incubation and decline stages of cyanobacteria, Pseudonocardia decreased significantly while Friedmanniella increased significantly in the early growth and outbreak stages. The abundance of phoD gene bacteria varies spatiotemporally, especially for its high spatial heterogeneity. The Ace and Shannon diversity index of phoD-harboring bacterial community during the early and outbreak stages of cyanobacteria were much higher than those in the incubation and decline stages. The changes of phoD-harboring bacterial community were mainly driven by APA, dissolved oxygen, chlorophyll-a, water temperature, total phosphorus and inorganic phosphorus. The rapid decline of dissolved inorganic phosphorus in overlying waters due to the increasing cyanobacterial photosynthesis in the early growth of cyanobacteria induces the APA, promotes the growth of Friedmanniella and alleviates the phosphorus restriction.

COVID-19 case doubling time associated with non-pharmaceutical interventions and vaccination: A global experience.

BackgroundEvidence has revealed that nonpharmaceutical interventions (NPIs) were effective in attenuating the spread of COVID-19. However, policymakers have encountered difficulty in identifying the most effective policies under different circumstances. This study investigated the relative effectiveness of different NPIs and vaccination in prolonging COVID-19 case doubling time (DT).MethodsThe study sample consisted of observations from 137 countries during 1 January 2020 to 13 June 2021. DT was calculated on a daily basis per country. Data were retrieved from the Oxford COVID-19 Government Response Tracker, World Development Indicators, and Worldwide Governance Indicators. To capture policy intervention dynamics, we combined a random-effect growth-curve model with nonstandard interrupted time series analysis. We also evaluated the association of policy measures with DT for different outbreak stages and levels of government effectiveness.ResultsVaccine rollouts, workplace closures, and school closures were relatively effective. For each day that these measures were implemented, the DT increased by 1.96% (95% confidence interval (CI) = 0.63 to 3.29; P = 0.004), 1.41% (95% CI = 0.88 to 1.95%; P < 0.001) and 1.38% (95% CI = 0.95 to 1.81%; P < 0.001), respectively. Workplace and school closures were positively associated with DT at all stages; however, the associations weakened in later stages, where vaccine rollouts appeared to be most effective in prolonging DT (95% CI = 1.51% to 3.04%; P < 0.05). For countries with a high level of government effectiveness, most of the containment measures evaluated were effective; vaccine rollouts had the greatest effect size. For countries with medium or low levels of government effectiveness, only the closure of workplaces was consistently associated with prolonged DT.ConclusionsThe effectiveness of vaccine rollouts outweighed that of NPIs, especially in the later outbreak stages. However, vaccination was not associated with prolonged case DT in countries with lower levels of government effectiveness, probably due to low vaccine coverage. Among the NPIs examined, workplace closures were highly effective across all outbreak stages and levels of government effectiveness. Our findings suggest that mass vaccination is critical to reducing SARS-CoV-2 transmission, especially in countries where NPIs are less effective.

The Saudi Ministry of Health's Twitter Communication Strategies and Public Engagement During the COVID-19 Pandemic: Content Analysis Study.

BackgroundDuring a public health crisis such as the current COVID-19 pandemic, governments and health authorities need quick and accurate methods of communicating with the public. While social media can serve as a useful tool for effective communication during disease outbreaks, few studies have elucidated how these platforms are used by the Ministry of Health (MOH) during disease outbreaks in Saudi Arabia.ObjectiveGuided by the Crisis and Emergency Risk Communication model, this study aimed to explore the MOH’s use of Twitter and the public’s engagement during different stages of the COVID-19 pandemic in Saudi Arabia.MethodsTweets and corresponding likes and retweets were extracted from the official Twitter account of the MOH in Saudi Arabia for the period of January 1 through August 31, 2020. Tweets related to COVID-19 were identified; subsequently, content analysis was performed, in which tweets were coded for the following message types: risk messages, warnings, preparations, uncertainty reduction, efficacy, reassurance, and digital health responses. Public engagement was measured by examining the numbers of likes and retweets. The association between outbreak stages and types of messages was assessed, as well as the effect of these messages on public engagement.ResultsThe MOH posted a total of 1393 original tweets during the study period. Of the total tweets, 1293 (92.82%) were related to COVID-19, and 1217 were ultimately included in the analysis. The MOH posted the majority of its tweets (65.89%) during the initial stage of the outbreak. Accordingly, the public showed the highest level of engagement (as indicated by numbers of likes and retweets) during the initial stage. The types of messages sent by the MOH significantly differed across outbreak stages, with messages related to uncertainty reduction, reassurance, and efficacy being prevalent among all stages. Tweet content, media type, and crisis stage influenced the level of public engagement. Engagement was negatively associated with the inclusion of hyperlinks and multimedia files, while higher level of public engagement was associated with the use of hashtags. Tweets related to warnings, uncertainty reduction, and reassurance received high levels of public engagement.ConclusionsThis study provides insights into the Saudi MOH’s communication strategy during the COVID-19 pandemic. Our results have implications for researchers, governments, health organizations, and practitioners with regard to their communication practices during outbreaks. To increase public engagement, governments and health authorities should consider the public’s need for information. This, in turn, could raise public awareness regarding disease outbreaks.