Source Of Epidemics Research Articles

Construction and application of a staged early warning model for dengue fever

To achieve early warning of dengue fever from multiple sources and improve the ability to detect and identify dengue fever outbreaks timely, we took Hangzhou as an example and proposed the possibility of early warning of dengue fever. This study divided early warning of dengue fever into three stages: early warning of epidemic source, epidemic symptom, and epidemic. The early warning of epidemic source and epidemic symptom were emphasized to provide reference for other similar studies. Our findings showed that the staged warning of dengue fever was meaningful. Combining the source early warning with the symptom early warning could improve the sensitivity of the warning. Monthly warning can be used as a supplement to weekly warning.

A Socio-Political Aspect of Housing and Communal Sanitation in the USSR, 1950s–1960s (Based on Materials of Leningrad and Vyborg)

Introduction. The article examines the interactions between the sanitary service, other departments, and city residents in the 1950s and 1960s to improve sanitary conditions, using the examples of Leningrad and Vyborg. It shows how the level of housing safety increased as the state allocated material resources to service organizations and improved sanitary standards. Methods and materials. The article is based on materials from the State Archive of the Russian Federation, the Central City Archive of St. Petersburg, and the Leningrad Oblast Archive, and a number of newspaper publications. Minutes of meetings, reports and explanatory notes, and citizens’ appeals to various authorities show that littered exits, uncollected cesspools, irregular cleaning of adjoining territories, and mountains of garbage often became a source of epidemics. Analysis. These problems were addressed as communication between government agencies and the public evolved. The legislative framework governing sanitary safety in cities was formed as early as the 1930s. The situation was aggravated by the lack of education of the population, which did not want to comply with sanitary rules. Solving the problem required concerted work by authorities, academics, and community activists. In order to reduce the risks of disease for city residents, city authorities organized trash pickups, lectures for citizens with representatives of sanitation services, etc. Thus, practices were formed to maintain compliance with the necessary norms. Results. The identified features of the implementation of housing and communal sanitation norms give the idea that established communication between government and public organizations was a channel for reducing the risks of epidemics and the comfort of the dwelling. Increased use of specialized machinery that allowed for garbage collection and a number of other problems was able to accelerate sanitation problems. This article illustrates how the risks – the high likelihood of epidemics – forced the state and citizens to seek effective ways to develop and maintain sanitary standards. The successful development of practices was thus related to the development of the necessary infrastructure and the awareness of city residents of the benefits of complying with practices.

Genetic Diversity and Population Structure of Bursaphelenchus xylophilus in Guangdong, Guangxi, and Jiangsu Provinces in China

This study aimed to investigate the genetic structures of pine wood nematodes (PWNs, Bursaphelenchus xylophilus (Steiner & Buhrer) Nickle)), in Guangdong (GD), Guangxi (GX), and Jiangsu (JS) Provinces (the major PWN dispersal centers). Furthermore, we also explored potential migration routes among the different provinces in order to provide insights into the epidemic source of PWNs in the three provinces in China. We re-sequenced a total of 241 PWNs collected from the above provinces using next-generation sequencing to obtain raw genomic data. Bioinformatics analysis was used to identify the SNPs, genetic structures, and selective sweeps of the PWNs. The results indicate that the PWNs from these three provinces can be classified into five groups (A, B, C, D, and E), among which the genetic variations are significant. All PWN strains from JS were exclusively found in Group A. The PWNs in Groups B and C were composed of strains from GD and GX, while Groups D and E comprised only GD strains. Introgression analysis identified two possible pathways: (1) from Group A to Group B-GX and (2) from Group E to Group D. Selective sweep analysis showed that in Groups B and C, the candidate genes of Group B were mainly related to pectin lyase activity.

Genetic characterization and molecular epidemiological analysis of enterovirus C99 in China.

Enterovirus C99 (EV-C99) is a newly identified EV serotype within the species Enterovirus C. Few studies on EV-C99 have been conducted globally. More information and research on EV-C99 are needed to assess its genetic characteristics, phylogenetic relationships, and associations with enteroviral diseases. Here, the phylogenetic characteristics of 11 Chinese EV-C99 strains have been reported. The full-length genomic sequences of these 11 strains show 79.4-80.5% nucleotide identity and 91.7-94.3% amino acid (aa) identity with the prototype EV-C99. A maximum likelihood phylogenetic tree constructed based on the entire VP1 coding region identified 13 genotypes (A-M), revealing a high degree of variation among the EV-C99 strains. Phylogeographic analysis showed that the Xinjiang Uygur Autonomous Region is an important source of EV-C99 epidemics in various regions of China. Recombination analysis revealed inter-serotype recombination events of 16 Chinese EV-C99 strains in 5' untranslated regions and 3D regions, resulting in the formation of a single recombination form. Additionally, the Chinese strain of genotype J showed rich aa diversity in the P1 region, indicating that the genotype J of EV-C99 is still going through variable dynamic changes. This study contributes to the global understanding of the EV-C99 genome sequence and holds substantial implications for the surveillance of EV-C99.

Identifying Onion Fields at Risk of Iris Yellow Spot Virus in New York.

Iris yellow spot virus (IYSV) poses a significant threat to dry bulb onion, Allium cepa L., production and can lead to substantial yield reductions. IYSV is transmitted by onion thrips, Thrips tabaci (Lindeman), but not via seed. Transplanted onion fields have been major early season sources of IYSV epidemics. As onion thrips tend to disperse short distances, seeded onion fields bordering transplanted onion fields may be at greater risk of IYSV infection than seeded fields isolated from transplanted ones. Additionally, seeded onion fields planted early may be at greater risk of IYSV infection than those seeded later. In a 2-year study in New York, we compared IYSV incidence and onion thrips populations in seeded onion fields relative to their proximity to transplanted onion fields. In a second study, we compared IYSV incidence in onion fields with either small or large plants during midseason. Results showed similar IYSV incidence and onion thrips populations in seeded onion fields regardless of their proximity to transplanted onion fields, while IYSV incidence was over four times greater in large onion plants than in small ones during midseason. These findings suggest a greater risk of onion thrips-mediated IYSV infection in onion fields with large plants compared with small ones during midseason and that proximity of seeded fields to transplanted ones is a poor indicator of IYSV risk. Our findings on IYSV spread dynamics provided valuable insights for developing integrated pest and disease management strategies for New York onion growers.

Cationic Porphyrins as Antimicrobial and Antiviral Agents in Photodynamic Therapy.

Antimicrobial photodynamic therapy (APDT) has received a great deal of attention due to its unique ability to kill all currently known classes of microorganisms. To date, infectious diseases caused by bacteria and viruses are one of the main sources of high mortality, mass epidemics and global pandemics among humans. Every year, the emergence of three to four previously unknown species of viruses dangerous to humans is recorded, totaling more than 2/3 of all newly discovered human pathogens. The emergence of bacteria with multidrug resistance leads to the rapid obsolescence of antibiotics and the need to create new types of antibiotics. From this point of view, photodynamic inactivation of viruses and bacteria is of particular interest. This review summarizes the most relevant mechanisms of antiviral and antibacterial action of APDT, molecular targets and correlation between the structure of cationic porphyrins and their photodynamic activity.

One health implications of fur farming

Fur farming involves the captive-breeding, rearing, and killing of between 85 – 100 million animals annually for their pelts. The purpose of this report is to summarise key areas of significance and concern regarding fur farming, and discuss these matters and their one-health considerations. We conducted primary literature searches using Google Scholar and PubMed that focused on issues of animal welfare, zoonoses and public health, and environmental impacts of fur farming, and examined 280 reports. We identified that at least 15 species are farmed for fur across at least 19 countries. We found 16 categories of animal welfare concern (e.g., deprivation, stress, abnormal behaviours, insanitary conditions, forced obesity, and high morbidity and mortality), 18 reported endemic pathogens and diseases with confirmed or potential zoonotic and cross-species implications (e.g., bacterial n = 6, viral n = 5, and parasitic n = 7), and four main categories of environmental concern (e.g., greenhouse gas emissions, invasive alien species, toxic chemicals, and eutrophication) associated with fur farming. Despite numerous efforts to systematically monitor and control animal welfare at fur farms, practices continue to fail to meet normal scientific principles and models used in other animal welfare situations. In our view, limited available data does not currently indicate that fur farms are major sources of zoonotic epidemics and pandemics. The environmental problems caused by fur farming are significant, and relate mainly to invasive species, toxic chemical release and eutrophication of water bodies. We offer some recommendations for monitoring and controlling particular fur farming practices, in line with many governments and other investigators we conclude that inherent problems are essentially unresolvable and advocate complete prohibitions on the sector.

Methods on COVID-19 Epidemic Curve Estimation During Emergency Based on Baidu Search Engine and ILI Traditional Surveillance in Beijing, China

Surveillance is an essential work on infectious diseases prevention and control. When the pandemic occurred, the inadequacy of traditional surveillance was exposed, but it also provided a valuable opportunity to explore new surveillance methods. This study aimed to estimate the transmission dynamics and epidemic curve of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BF.7 in Beijing under the emergent situation using Baidu index and influenza-like illness (ILI) surveillance. A novel hybrid model (multiattention bidirectional gated recurrent unit (MABG)–susceptible–exposed–infected–removed (SEIR)) was developed, which leveraged a deep learning algorithm (MABG) to scrutinize the past records of ILI occurrences and the Baidu index of diverse symptoms such as fever, pyrexia, cough, sore throat, anti-fever medicine, and runny nose. By considering the current Baidu index and the correlation between ILI cases and coronavirus disease 2019 (COVID-19) cases, a transmission dynamics model (SEIR) was formulated to estimate the transmission dynamics and epidemic curve of SARS-CoV-2. During the COVID-19 pandemic, when conventional surveillance measures have been suspended temporarily, cases of ILI can serve as a useful indicator for estimating the epidemiological trends of COVID-19. In the specific case of Beijing, it has been ascertained that cumulative infection attack rate surpass 80.25% (95% confidence interval (95% CI): 77.51%–82.99%) since December 17, 2022, with the apex of the outbreak projected to transpire on December 12. The culmination of existing patients is expected to occur three days subsequent to this peak. Effective reproduction number (Rt) represents the average number of secondary infections generated from a single infected individual at a specific point in time during an epidemic, remained below 1 since December 17, 2022. The traditional disease surveillance systems should be complemented with information from modern surveillance data such as online data sources with advanced technical support. Modern surveillance channels should be used primarily in emerging infectious and disease outbreaks. Syndrome surveillance on COVID-19 should be established to following on the epidemic, clinical severity, and medical resource demand.

NLSI: An innovative method to locate epidemic sources on the SEIR propagation model.

Epidemics pose a significant threat to societal development. Accurately and swiftly identifying the source of an outbreak is crucial for controlling the spread of an epidemic and minimizing its impact. However, existing research on locating epidemic sources often overlooks the fact that epidemics have an incubation period and fails to consider social behaviors like self-isolation during the spread of the epidemic. In this study, we first take into account isolation behavior and introduce the Susceptible-Exposed-Infected-Recovered (SEIR) propagation model to simulate the spread of epidemics. As the epidemic reaches a certain threshold, government agencies or hospitals will report the IDs of some infected individuals and the time when symptoms first appear. The reported individuals, along with their first and second-order neighbors, are then isolated. Using the moment of symptom onset reported by the isolated individuals, we propose a node-level classification method and subsequently develop the node-level-based source identification (NLSI) algorithm. Extensive experiments demonstrate that the NLSI algorithm is capable of solving the source identification problem for single and multiple sources under the SEIR propagation model. We find that the source identification accuracy is higher when the infection rate is lower, and a sparse network structure is beneficial to source localization. Furthermore, we discover that the length of the isolation period has little impact on source localization, while the length of the incubation period significantly affects the accuracy of source localization. This research offers a novel approach for identifying the origin of the epidemic associated with our defined SEIR model.

Active querying approach to epidemic source detection on contact networks

The problem of identifying the source of an epidemic (also called patient zero) given a network of contacts and a set of infected individuals has attracted interest from a broad range of research communities. The successful and timely identification of the source can prevent a lot of harm as the number of possible infection routes can be narrowed down and potentially infected individuals can be isolated. Previous research on this topic often assumes that it is possible to observe the state of a substantial fraction of individuals in the network before attempting to identify the source. We, on the contrary, assume that observing the state of individuals in the network is costly or difficult and, hence, only the state of one or few individuals is initially observed. Moreover, we presume that not only the source is unknown, but also the duration for which the epidemic has evolved. From this more general problem setting a need to query the state of other (so far unobserved) individuals arises. In analogy with active learning, this leads us to formulate the active querying problem. In the active querying problem, we alternate between a source inference step and a querying step. For the source inference step, we rely on existing work but take a Bayesian perspective by putting a prior on the duration of the epidemic. In the querying step, we aim to query the states of individuals that provide the most information about the source of the epidemic, and to this end, we propose strategies inspired by the active learning literature. Our results are strongly in favor of a querying strategy that selects individuals for whom the disagreement between individual predictions, made by all possible sources separately, and a consensus prediction is maximal. Our approach is flexible and, in particular, can be applied to static as well as temporal networks. To demonstrate our approach’s practical importance, we experiment with three empirical (temporal) contact networks: a network of pig movements, a network of sexual contacts, and a network of face-to-face contacts between residents of a village in Malawi. The results show that active querying strategies can lead to substantially improved source inference results as compared to baseline heuristics. In fact, querying only a small fraction of nodes in a network is often enough to achieve a source inference performance comparable to a situation where the infection states of all nodes are known.

The phenomenon of urbanisation from a public health perspective. Urban spaces as a possible source of epidemics and pandemics caused by an infectious disease

Introduction
 Urbanisation is a global process leading to development of urban infrastructure and thus an increase in the population of urban areas. Health threats, including epidemics of infectious diseases that may break out in growing urban areas, can spread quickly and their effects could spread outside of the local territory. 
 Purpose
 To outline the relationship between globalising, post-modern urbanisation processes, in particular the specific form of extended urbanisation, and the risks posed by infectious diseases that could give rise to new epidemics or pandemics.
 State of knowledge
 Health risks occurring at the local level of an urban area react to, and simultaneously affect, health situation occurring at an indefinite distance from the original site of the event. An important impact on the situation are the expanding or newly emerging urban areas, which cause negative changes in social conditions, and the increase in spatial mobility of the global population, which facilitates the spread of infectious diseases.
 Summary
 Understanding 21st century urban trends is the key to improving collective health. Adopting a "public health perspective" regarding values and attitudes towards social phenomena and reality, as well as the necessary methods of conduct, seems to be one of the main challenges of the current era in which people around the world, regardless of the country's development status and level of resources, currently live in within one “ecosystem of infectious diseases”. Planned and controlled urbanization, taking into account the achievements of modern epidemiology, including molecular epidemiology, will help will help along the remediation of the cities of the future.

Epicenter of random epidemic spanning trees on finite graphs

Epidemic source detection is the problem of identifying the network node that originated an epidemic from a partial observation of the epidemic process. The problem finds applications in different contexts, such as detecting the origin of rumors in online social media, and has been studied under various assumptions. Different from prior studies, this work considers an epidemic process on a finite graph that starts on a random node (epidemic source) and terminates when all nodes are infected, yielding a rooted and directed epidemic tree that encodes node infections (i.e., a directed spanning tree of the graph with every edge directed away from the epidemic source). Assuming knowledge of the underlying graph and the undirected spanning tree (i.e., the infection edges but not their directions), can the epidemic source be accurately identified? This work tackles this problem by introducing the epicenter, an efficient estimator for the epidemic source, and thus, the direction of every edge in the epidemic tree. When the underlying graph is vertex-transitive the epicenter can be computed in linear time and it coincides with the well-known distance center of the epidemic tree. Moreover, on a complete graph the epicenter is also the most likely estimator for the source. Finally, the accuracy of the epicenter is evaluated numerically on five different graph models and the performance strongly depends on the graph structure, varying from 31% (on complete graphs) to 13% (on sparse power-law graphs). However, for all graph models considered the epicenter exhibited an accuracy higher than the distance center, being three times more accurate on sparse power-law graphs.

The Construction and Application of Dynamic Population Database Based on “Suishenma Code”

The construction and application of dynamic population database based on“Suishenma code”,Based on the community, units, buildings, residential areas, residential buildings and public places existing “changsuo code”. It makes use of image recognition, wireless encryption, big data and cloud storage technology to make it become the terminal of mobile personnel data collection, recognition and processing analysis. Meanwhile, the real-time dynamic matching database of people and houses is recorded and generated to form the corresponding relationship between people and places of activity. The construction of the system mainly covers the interior of buildings such as residential areas, units and houses with intensive human activities, social cases and high incidence of livelihood cases, make up the"Xueliang、 Tianyan、Anke Project" monitoring blind spots, and can be used for the prevention and control of the epidemic and other emergencies trace source and early warning. The construction of this program serves the following areas: Tianyan project, major emergencies, housing management, special crowd management, public publicity, residents services and government services.

Psychological Analysis on Network Rumors Spread in COVID-19 Epidemic.

Since the outbreak of the COVID-19 epidemic, related rumors have been spread rapidly on social media, which has seriously affected public normal life and caused mental panic and anxiety. This paper, by analyzing the spread of online rumors and their impact on public mental health during the COVID-19 epidemic, aims to put forward relevant suggestions for dealing with rumors and improving public mental health. According to the actual rumors collected during the epidemic period as the content of the questionnaire, an online rumor survey was carried out. A total of 1,200 questionnaires were distributed, and 1,165 valid questionnaires were collected. Among the sources of information about the epidemic, 78.2% of the respondents obtained epidemic information through online channels. 633 respondents were concerned about the epidemic situation, accounting for 54.3%. The respondents have different susceptibility to the epidemic sources, epidemic spread, epidemic treatment, epidemic influence, and epidemic prevention. They account for 37.2%, 43. 4%, 45.2%, 39.4%, and 46.1% respectively. 646 respondents expressed great anxiety about the epidemic situation, accounting for 55.5%. The source (t=26.33, P<0.05), transmission (t=28.32, P<0.05), prevention (t=35.36, P<0.05), treatment (t=40.32, P<0.05), and impact of the epidemic (t=42.01, P<0.05) can significantly predict the transmission intention. To control the spread of epidemic rumors and reduce the negative impact of such information on public mental health, the government and various walks of life need to collaborate to solve the problem from the aspects of information disclosure system, supervision means, and network communication system.

Advances in SARS-CoV-2 diagnostic strategies during the later COVID-19 era

Based on natural infection or vaccination, the protective barrier for population has been preliminarily established. However, with constant appearances of SARS-CoV-2 variants, breakthrough infection events cannot be completely avoided, and thus the diagnostic strategy is still the key to discovering epidemic sources and blocking the transmission chain. Currently, SARS-CoV-2 diagnosis technologies based on nucleic acid, antigen and antibody detections have developed and extended in diversity. Under the background of work resumption and epidemic-prevention normalization during the later COVID-19 era, it is necessary for us to choose appropriate detection methods to satisfy the need of epidemic prevention and control in various scenarios. We summarized the principles and applicable characteristics of existing SARS-CoV-2 detection technologies in this paper, aimed to provide guidance for clinical and public health personnel to make targeted decisions.

Abstract 3687: Implementing geospatial technology to understand the prostate cancer health burdens and socioeconomic status in Alabama

Abstract Socioeconomic status and health disparities are a significant liability for the prevalence of many diseases, including cancer. Among many contributing factors, lack of socioeconomic advancement and inequality in resource distribution is closely associated with prostate cancer occurrence. The State of Alabama has one of the highest rates of prostate cancer in the nation and the third cancer epidemic at the state level. Due to widespread disparities in infrastructure development, political willpower, equal healthcare, and education opportunity, Alabama's Black Belt region has been further divided by socioeconomic statuses among the majority (Whites) and minority (African American) populations. The purpose of this research is to recognize Alabama's health burdens and socioeconomic status using geo-spatial technology (GIS) to examine prostate cancer health disparity. GIS has become a valuable decision-making tool in understanding the public health care sectors, including prostate cancer prevalence. GIS supports assembling spatial and non-spatial data, displays the spatial distribution of health disparities, and underlines further interconnectivity of policy-related questions. This research incorporates county-level prostate cancer data using GIS and outlining the correlation between prostate cancer prevalence and socioeconomic factors to understand Alabama's cancer health disparity and equity. A combination of socioeconomic factors and state and federal-level cancer epidemic data sources underline Alabama's black belt region (predominantly African American) prostate cancer prevalence is higher than the non-black belt. The GIS analysis demonstrated that effective cancer prevention programs are needed to eliminate health disparities and enhance health equity among underserved populations of Alabama. Citation Format: Ram Alagan, Seela Aladuwaka, Rajesh Singh, Upender Manne, Manoj K. Mishra. Implementing geospatial technology to understand the prostate cancer health burdens and socioeconomic status in Alabama [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3687.

#69 Viral Respiratory Infections in Children in a Resource Limited Setting

BackgroundChildren under 5 years of age bear the highest burden of severe disease from respiratory illness. Surveillance of respiratory viral infections in hospitalized children informs local burden of disease and may assist in identifying potential sources of epidemics. In resource-limited countries, like Haiti, lack of infrastructure, resources, and oversight are barriers for such surveillance programs. Just before the onset of the pandemic in December 2019, we completed the preparation to implement a respiratory surveillance program at Hôpital Saint Damien (HSD). Furthermore, other major events such as a 7.2 magnitude earthquake and the assassination of the president of Haiti had an impact on the political and economic stability of the country, impacting the hospital and this study. Despite these challenges, we report the preliminary findings of a hospital-based surveillance program of severe acute respiratory illness (SARI) in children at a mother and child hospital in Tabarre, Haiti.MethodParticipants were included if they were < 18 years of age; met the World Health Organization definition for SARI, which includes presence of 1) cough, 2) history of fever or measured fever ≥ 38 C°, 3) onset within the last 10 days, and 4) requirement of hospitalization; and consented to participate. We collected demographic and clinical data for enrolled patients and obtained a nasopharyngeal swab sample. Samples were rapid tested for influenza A, influenza B, respiratory syncytial virus (RSV), and SARS-CoV-2 and stored and shipped for genomic sequencing.ResultsAs of January 6th, 2022, we had enrolled and tested 143 patients who presented to the hospital with SARI. Of these cases, 31 were RSV-positive, 7 were positive for influenza B-positive, 1 was positive for influenza A-positive, and 1 was SARS-CoV-2-positive. 97 cases are currently available for descriptive analysis, with 10 RSV-positive cases, 2 influenza B-positive cases, and 1 SARS-CoV-2-positive case. 55% (n= 53) of participants are male, with an average age of 2 years (standard deviation = 2.8 years). Along with fever and cough, 18% (n=17) presented with wheezing, 60% (n=58) presented with shortness of breath, 37% (n=36) presented with tachypnea, 7% (n=7) presented with nasal congestion, 1% (n=1) had a sore throat, 2% (n=2) had nausea, 7% (n=7) were lethargic, and 9% (n=9) had diarrhea. Nearly all enrolled children, 99% (n=96) live in households where coal or biofuel is used for cooking indoors. In regard to type of respiratory tract infection (RTI), 18% (n=17) were upper RTI, 30% (n=29) were lower RTI, and 53% (n=51) were both upper and lower RTI. While sequencing of influenza A and B isolates remains to be conducted, sequencing for the SARS-CoV-2 sample revealed the isolate to be of P.1 lineage.ConclusionIn children requiring hospital admission for SARI, our limited testing identified 40 children with respiratory viruses that were circulating during the SARS-CoV-2 pandemic. Identifying these viruses can support healthcare providers to provide better preventions measures, including compliance with vaccination, and administering appropriate therapeutics, such as antibiotics. Further testing with additional primers against other pathogens will be conducted to identify other potential causes of illness.

Spatial aggregation choice in the era of digital and administrative surveillance data.

Traditional disease surveillance is increasingly being complemented by data from non-traditional sources like medical claims, electronic health records, and participatory syndromic data platforms. As non-traditional data are often collected at the individual-level and are convenience samples from a population, choices must be made on the aggregation of these data for epidemiological inference. Our study seeks to understand the influence of spatial aggregation choice on our understanding of disease spread with a case study of influenza-like illness in the United States. Using U.S. medical claims data from 2002 to 2009, we examined the epidemic source location, onset and peak season timing, and epidemic duration of influenza seasons for data aggregated to the county and state scales. We also compared spatial autocorrelation and tested the relative magnitude of spatial aggregation differences between onset and peak measures of disease burden. We found discrepancies in the inferred epidemic source locations and estimated influenza season onsets and peaks when comparing county and state-level data. Spatial autocorrelation was detected across more expansive geographic ranges during the peak season as compared to the early flu season, and there were greater spatial aggregation differences in early season measures as well. Epidemiological inferences are more sensitive to spatial scale early on during U.S. influenza seasons, when there is greater heterogeneity in timing, intensity, and geographic spread of the epidemics. Users of non-traditional disease surveillance should carefully consider how to extract accurate disease signals from finer-scaled data for early use in disease outbreaks.

Phylogeography and evolutionary dynamics analysis of porcine delta-coronavirus with host expansion to humans.

From 2003 onwards, three pandemics have been caused by coronaviruses: severe acute respiratory syndrome coronavirus (SARS-CoV); middle east respiratory syndrome coronavirus (MERS-CoV); and, most recently, SARS-CoV-2. Notably, all three were transmitted from animals to humans. This would suggest that animals are potential sources of epidemics for humans. The emerging porcine delta-coronavirus was reported to infect children. This is a red flag that marks the ability of PDCoV to break barriers of cross-species transmission to humans. Therefore, we conducted molecular genetic analysis of global clade PDCoV to characterize spatiotemporal patterns of viral diffusion and genetic diversity. PDCoV was classified into three major lineages, according to distribution and phylogenetic analysis of PDCoV. It can be inferred based on the analysis results of the currently known PDCoV strains that PDCoV might originate in Asia. We also selected six special spike amino acid sequences to align and analyze to find seven significant mutation sites. The accumulation of these mutations may enhance dynamic movements, accelerating spike protein membrane fusion events and transmission. Altogether, our study offers a novel insight into the diversification, evolution, and interspecies transmission and origin of PDCoV and emphasizes the need to study the zoonotic potential of the PDCoV and comprehensive surveillance and enhanced biosecurity precautions for PDCoV.

RNA-Seq and Gene Regulatory Network Analyses Uncover Candidate Genes in the Early Defense to Two Hemibiotrophic Colletorichum spp. in Strawberry.

Two hemibiotrophic pathogens, Colletotrichum acutatum (Ca) and C. gloeosporioides (Cg), cause anthracnose fruit rot and anthracnose crown rot in strawberry (Fragaria × ananassa Duchesne), respectively. Both Ca and Cg can initially infect through a brief biotrophic phase, which is associated with the production of intracellular primary hyphae that can infect host cells without causing cell death and establishing hemibiotrophic infection (HBI) or quiescent (latent infections) in leaf tissues. The Ca and Cg HBI in nurseries and subsequent distribution of asymptomatic infected transplants to fruit production fields is the major source of anthracnose epidemics in North Carolina. In the absence of complete resistance, strawberry varieties with good fruit quality showing rate-reducing resistance have frequently been used as a source of resistance to Ca and Cg. However, the molecular mechanisms underlying the rate-reducing resistance or susceptibility to Ca and Cg are still unknown. We performed comparative transcriptome analyses to examine how rate-reducing resistant genotype NCS 10-147 and susceptible genotype ‘Chandler’ respond to Ca and Cg and identify molecular events between 0 and 48 h after the pathogen-inoculated and mock-inoculated leaf tissues. Although plant response to both Ca and Cg at the same timepoint was not similar, more genes in the resistant interaction were upregulated at 24 hpi with Ca compared with those at 48 hpi. In contrast, a few genes were upregulated in the resistant interaction at 48 hpi with Cg. Resistance response to both Ca and Cg was associated with upregulation of MLP-like protein 44, LRR receptor-like serine/threonine-protein kinase, and auxin signaling pathway, whereas susceptibility was linked to modulation of the phenylpropanoid pathway. Gene regulatory network inference analysis revealed candidate transcription factors (TFs) such as GATA5 and MYB-10, and their downstream targets were upregulated in resistant interactions. Our results provide valuable insights into transcriptional changes during resistant and susceptible interactions, which can further facilitate assessing candidate genes necessary for resistance to two hemibiotrophic Colletotrichum spp. in strawberry.