Find research datasets worth reusing

opencc-by-4.0Apr 2020View details →

Dataset and images for "Instantaneous R calculation for COVID-19 epidemic in Brazil"

This dataset was generated from raw data obtained at  <ul> <li>Ceará State - <a href="https://indicadores.integrasus.saude.ce.gov.br/api/casos-coronavirus/export-csv">https://indicadores.integrasus.saude.ce.gov.br/api/casos-coronavirus/export-csv</a></li> <li>São Paulo State - <a href="http://www.seade.gov.br/wp-content/uploads/2020/04/Dados-covid-19-estado.csv">http://www.seade.gov.br/wp-content/uploads/2020/04/Dados-covid-19-estado.csv</a></li> <li>Brazil - <a href="https://covid.saude.gov.br/">https://covid.saude.gov.br/</a></li> </ul> Data was processed with R package EpiEstim (methodology in the associated preprint). Briefly, instantaneous R was estimated within a 5 day time window. Prior mean and standard deviation values for R were set at 3 and 1. Serial interval was estimated using a parametric distribution with uncertainty (offset gamma). We compared the results at two time points (day 7 and day 21 after the first case was registered at each region) from different brazillian states in order to make inferences about the epidemic dynamics.

opengpl-2.0Nov 2014View details →

Sudden_Oak_Death_in_Oregon_Forests: Spatial and temporal population dynamics of the sudden oak death epidemic in Oregon Forests

Release of code associated with the submitted manuscript Authors ZN Kamvar, MM Larsen, AM Kanaskie, EM Hansen, and NJ Grünwald. Title Spatial and temporal population dynamics of the sudden oak death epidemic in Oregon Forests.

opencc-by-4.0Feb 2024View details →

WKU experimental epidemic game using research version of Operation Outbreak app

This dataset contains the full list of participants and events in the experimental epidemic game at Wenzhou-Kean University (WKU) in China, run between November 20 and December 4 of 2023 using a customized version of the Operation Outbreak mobile app and cloud backend for research uses. The following blog post provides some more information about this simulation: https://colabobio.medium.com/667295c43907

opencc-by-4.0May 2022View details →

Massive Health Education through Technological Mediation: analyzes and impacts on the syphilis epidemic in Brazil

Repository  Dataset name: avasus_syphilis_trail_dataset.csv  Version: 1.0  Dataset period: 05/12/2016 - 01/14/2022  Dataset Characteristics: Multivalued  Number of Instances: 177732  Number of Attributes: 16  Missing Values: Yes  Area(s): Health and education  Sources:  <ul> <li> Virtual Learning Environment of the Brazilian Health System (AVASUS) (Brasil, 2022a);  </li> <li> Brazilian Occupational Classification (CBO) (Brasil, 2022b); </li> <li> National Registry of Health Establishments (CNES) (Brasil, 2022c). </li> </ul> Description: The data contained in the avasus_syphilis_trail_dataset.csv dataset (see Table 1) originate from AVASUS users who have taken a course on the “Syphilis and other STI” learning path. This dataset provides elemental data to analyze the impact and reach of the trails and the profile of their participants. Table 1: Description of Dataset Features.  <table> <tbody> <tr> <td> Attributes  </td> <td> Description  </td> <td> datatype  </td> <td> Value </td> <td> Source </td> </tr> <tr> <td> user_id </td> <td> Unique identifier of the user (anonymously). </td> <td> Numerical.  </td> <td> Randomly generated integer. </td> <td> AVASUS. </td> </tr> <tr> <td> user_gender </td> <td> Gender of the user.  </td> <td> Categorical.  </td> <td> Feminino / Masculino / Não Informado. (In English: Female, Male or Uninformed) </td> <td> AVASUS. </td> </tr> <tr> <td> user_occupation </td> <td> User occupation </td> <td> Categorical.  </td> <td> Text coded according to the Brazilian Classification of Occupations or “Indivíduo sem afiliação formal.” (In English “Individual without formal affiliation.”) </td> <td> CNES. </td> </tr> <tr> <td> user_cnes </td> <td> The CNES code refers to the health establishment where the user works. </td> <td> Numerical. </td> <td> CNES Code or NaN. </td> <td> CNES. </td> </tr> <tr> <td> user_level_attention </td> <td> Identification of the health care network level for which the user works. </td> <td> Categorical. </td> <td> “ATENCAO PRIMARIA”,   “MEDIA COMPLEXIDADE”,    “ALTA COMPLEXIDADE”,    and their possible combinations.   (In English "PRIMARY HEALTH CARE", "SECONDARY HEALTH CARE" AND "TERTIARY HEALTH CARE")   Or NaN. </td> <td> CNES. </td> </tr> <tr> <td> user_region </td> <td> Brazilian region in which the user resides. </td> <td> Categorical.  </td> <td> Brazilian region according to IBGE: Norte, Nordeste, Centro-Oeste, Sudeste or Sul (In English North, Northeast, Midwest, Southeast or South). Other options: “Exterior” or “Não Informado” (In English: Outside or Not informed). </td> <td> AVASUS. </td> </tr> <tr> <td> course_id </td> <td> Unique identifier of the course performed by the avasus user. </td> <td> Numerical.  </td> <td> Code list according to AVASUS. </td> <td> AVASUS. </td> </tr> <tr> <td> course_name </td> <td> Name of the course taken by the avasus user. </td> <td> Categorical. </td> <td> Course name according to AVASUS. </td> <td> AVASUS. </td> </tr> <tr> <td> course_workload </td> <td> Course timetable. </td> <td> Numerical. </td> <td> Range from 0 to 120. </td> <td> AVASUS. </td> </tr> <tr> <td> course_creation_date </td> <td> Course creation date. </td> <td> Date. </td> <td> “YYYY-MM-DD” or NaN. </td> <td> AVASUS. </td> </tr> <tr> <td> enrollment_id </td> <td> Unique identification of the enrollment carried out by the student in some course of the trail. </td> <td> Numerical.  </td> <td> Randomly generated single integer. </td> <td> AVASUS. </td> </tr> <tr> <td> enrollment_creation </td> <td> Date the student registered. </td> <td> Date. </td> <td> “YYYY-MM-DD” or NaN. </td> <td> AVASUS. </td> </tr> <tr> <td> enrollment_completion_date </td> <td> Date the student completed the course. </td> <td> Date. </td> <td> “YYYY-MM-DD” or NaN. </td> <td> AVASUS. </td> </tr> <tr> <td> enrollment_current_progress </td> <td> Student progress regarding course completion. </td> <td> Numerical. </td> <td> Range from 0 to 100.  </td> <td> AVASUS. </td> </tr> <tr> <td> enrollment_text_evaluation </td> <td> Comment made by the student about the course. </td> <td> Categorial.  </td> <td> Free text or NaN. </td> <td> AVASUS. </td> </tr> <tr> <td> enrollment_course_evaluation </td> <td> A score given to the course by the participant. </td> <td> Numerical. </td> <td> 0, 1, 2, 3, 4, 5 or NaN. </td> <td> AVASUS. </td> </tr> </tbody> </table>   References  [1] Brasil (2022a). Ambiente virtual de aprendizagem do sus - avasus. atenção à saúde da pessoa privada de liberdade Available from: https://avasus.ufrn.br/local/avasplugin/cursos/curso.php?id=114 .  [2] Brasil (2022b). Classificação brasileira de ocupações - CBO. Available from: http://www.mtecbo.gov.br/cbosite/pages/home.jsf .  [3] Brasil (2022c). Cadastro nacional de estabelecimentos de saúde - CNES. Available from: http://cnes.datasus.gov.br/ . Article:  Massive Health Education with Technological Mediation: analyzes and impacts on the syphilis epidemic in Brazil

opencc-by-4.0Jan 2022View details →

An epidemiological overview of the equine influenza epidemic in Great Britain during 2019: Dataset

This repository contains datasets and code used for the manuscript as titled. All details regarding the data source and considerations that should be noted are discussed in the manuscript. Referencing this dataset Fleur Whitlock, John Grewar & J. Richard Newton (2022) An epidemiological overview of the equine influenza epidemic in Great Britain during 2019 [Dataset]. University of Cambridge. <a href="https://doi.org/10.5281/zenodo.5886153">https://doi.org/10.5281/zenodo.7010228</a>

opencc-by-4.0Jun 2020View details →

Symptoms in health care workers during the COVID-19 epidemic. A cross-sectional survey.

data collected during the COVID-19 epidemics on workers of the Health Care Unit Roma4, Civitavecchia. Paper submitted.

opencc-zeroJun 2020View details →

Adaptive changes in the genomes of wild rabbits after 16 years of viral epidemics

Since its introduction to control overabundant alien rabbits (Oryctolagus cuniculus), the highly virulent Rabbit Haemorrhagic Disease Virus (RHDV) has caused regular annual disease outbreaks in Australian rabbit populations. Although initially reducing rabbit abundance by 60%, continent-wide, experimental evidence has since indicated increased genetic resistance in wild rabbits that have experienced RHDV-driven selection. To identify genetic adaptations, which explain the increased resistance to this biocontrol virus, we investigated genome-wide SNP (single nucleotide polymorphism) allele frequency changes in a South Australian rabbit population that was sampled in 1996 (pre-RHD genomes) and after 16 years of RHDV outbreaks. We identified several SNPs with changed allele frequencies within or in proximity of genes that have roles potentially important for increased RHD resistance. Many of the identified genes are known to be involved in virus infections or immunity, or had previously been identified as being differentially expressed in healthy vs. acutely RHDV-infected rabbits. Furthermore, we show in a simulation study that the allele/genotype frequency changes cannot be explained by drift alone, and that several candidate genes had also been identified as being associated with surviving RHD in a different Australian rabbit population. Our unique dataset allowed us to identify candidate genes for RHDV resistance that have evolved under natural conditions, and over a time span that would not have been feasible to study in an experimental setting. Moreover, it provides a rare example of host genetic adaptations to virus-driven selection in response to a suddenly emerging infectious disease.

opencc-zeroApr 2022View details →

Little Appleton Pasteuria epidemic dataset

Virulence, the degree to which a pathogen harms its host, is an important but poorly understood aspect of host-pathogen interactions. However it is not a static trait, instead depending on ecological context and potentially evolving over short periods of time (e.g., during the course of an epidemic). At the start of an epidemic, when susceptible hosts are plentiful, pathogens may evolve increased virulence, maximizing their intrinsic growth rate. However, if host density declines during an epidemic, theory predicts evolution of reduced virulence. Although well-studied theoretically, there is still little empirical evidence for virulence evolution in epidemics, especially in natural settings with native host and pathogen species. Here, we used a combination of field observations and lab experiments in the Daphnia-Pasteuria model system to look for evidence of virulence evolution in nature. Controlling for environmental conditions, we found that there was no change in parasite virulence when measured in terms of host lifespan or the number of clutches produced. There also was no evidence for evolution of host resistance or parasite infectivity. However, over the epidemic, the parasite evolved to produce significantly fewer spores in infected hosts, perhaps as a result of trade-offs quantified in earlier studies. Future studies that track evolution of parasite spore yield in more populations, and that link those changes with genetic changes and with predation rates, will yield better insight into the drivers of parasite evolution in the wild.

opencc-zeroJun 2022View details →

COVID-19 epidemic in Fiji

This study involves the estimation of a key epidemiological parameter for evaluating and monitoring the transmissibility of a disease. The time-varying reproduction number is the index for quantifying the transmissibility of infectious diseases. Accurate and timely estimation of the time-varying reproduction number is essential for optimising non-pharmacological interventions and movement control orders during epidemics. The time-varying reproduction number for the second wave of the pandemic in Fiji is estimated using the popular EpiEstim R package and the publicly available COVID-19 data from 19 April 2021 to 01 December 2021. Our findings show that the non-pharmacological interventions and movement control orders introduced and enforced by the Fijian Government had a significant impact in preventing the spread of COVID-19. Moreover, the results show that many restrictions were either relaxed or eased when the time-varying reproduction number was below the threshold value of 1. The results have equipped some information on the second wave of the COVID-19 pandemic that could be used in the future as a guide for public health policymakers in Fiji. Estimation of time-varying reproduction numbers would be helpful for continuous monitoring of the effectiveness of the current public health policies that are being implemented in Fiji.

opencc-by-4.0Dec 2013View details →

Fig. 2 in Pathologic findings in Western gray squirrels (Sciurus griseus) from a notoedric mange epidemic in the San Bernardino Mountains, California

Fig. 2. Histologic section of skin of a free-ranging western gray squirrel (Sciurus griseus) with notoedric mange. (a) Intraepidermal tunnels containing numerous mites [arrows]. H&E stain. Bar = 500 µm. [Brace = epidermis; star = dermis.] (b) High magnification demonstrating intralesional mites [arrows] and small numbers of round to oval eggs [arrowheads]. H&E stain. Bar = 100 µm.

opencc-by-4.0Dec 2013View details →

Fig. 1 in Pathologic findings in Western gray squirrels (Sciurus griseus) from a notoedric mange epidemic in the San Bernardino Mountains, California

Fig. 1. (a). Histologic sections of skin of free-ranging Western gray squirrels (Sciurus griseus). (a) Severe notoedric mange characterized by, irregular acanthosis with rete ridge formation, extensive orthokeratotic and parakeratotic hyperkeratosis with serocellular crusting, intracorneal pustules, and numerous variably-sized, intracorneal and intraepidermal tunnels. H&E stain. Bar = 1000 µm. (b) Unaffected skin for comparison. H & E stain. Bar = 500 µm. [Brace = epidermis; star = dermis.]

opencc-by-4.0Jun 2019View details →

SNP call data for: The current epidemic of the barley pathogen Ramularia collo-cygni derives from a recent population expansion and shows global admixture

Ramularia Leaf Spot is becoming an ever increasing problem in main barley growing regions since the 1980s, causing up to 70% yield loss in extreme cases. Yet, the causal agent Ramularia collo-cygni, remains poorly studied. The diversity of the pathogen in the field thus far remains unknown. Furthermore, it is unknown to which extend the pathogen has a sexual reproductive cycle. To date, the teleomorph of R. collo-cygni has not been observed. To study the genetic diversity of R. collo-cygni and to get more insights into its biology, we sequenced the genomes of 19 R. collo-cygni isolates from multiple geographic locations and diverse hosts. Here we share the SNP call data as well as the reference genome. The reference genome files and assembly can be found on ENI: GCA_900074925.1 https://www.ebi.ac.uk/ena/data/view/GCA_900074925.1 The raw sequence data is also available through ENI: ERX2296228 https://www.ebi.ac.uk/ena/data/view/ERX2296228

opencc-by-4.0Dec 2018View details →

Sentinel-2 Optical satellite imagery for Epidemic Disease Mapping

Sentinel-2 Optical satellite imagery for Epidemic Disease Mapping

opencc-by-4.0Dec 2020View details →

A Global Epidemics Dataset (1500-2020)

This is a Global Epidemics Dataset analyzed in: Marani, M. , G. Katul, W.H. Pan, A. Parolari, Intensity and frequency of extreme novel epidemics, 2021 The upload includes a revised code that corrects an error and produces revised estimates of the probability of occurrence of global epidemics in the present and in the future.

opencc-zeroJun 2023View details →

Data for: Age structure eliminates the impact of coinfection on epidemic dynamics in a freshwater zooplankton system

Parasites often coinfect host populations, and, by interacting within hosts, might change the trajectory of multi-parasite epidemics. However, host-parasite interactions often change with host age, raising the possibility that within-host interactions between parasites might also change, influencing the spread of disease. We measured how heterospecific parasites interacted within zooplankton hosts and how host age changed these interactions. We then parameterized an epidemiological model to explore how age-effects altered the impact of coinfection on epidemic dynamics. In our model, we found that in populations where epidemiologically relevant parameters did not change with age, the presence of a second parasite altered epidemic dynamics. In contrast, when parameters varied with host age (based on our empirical measures), there was no longer a difference in epidemic dynamics between singly and coinfected populations, indicating that variable age structure within a population eliminates the impact of coinfection on epidemic dynamics. Moreover, infection prevalence of both parasites was lower in populations where epidemiologically relevant parameters changed with age. Given that host-population age structure changes over time and space, these results indicate that age-effects are important for understanding epidemiological processes in coinfected systems and that studies focused on a single age group could yield inaccurate insights.

opencc-zeroJul 2023View details →

Data for: The role of temperature in the start of seasonal infectious disease epidemics

Many infectious diseases display strong seasonal dynamics. When both hosts and parasites are influenced by seasonal variables, it is unclear if the start of an epidemic is limited by host or parasite factors or both. The Daphnia-Pasteuria host-parasite system exhibits seasonal epidemics. We aimed to ascertain how temperature contributes to the timing of P. ramosa epidemics in early spring. To this aim, we experimentally disentangled this effect from the effects of temperature on host development and phenology and from that of host traits on parasite time to visible infection. We hypothesized that the parasite is additionally directly limited by low temperatures beyond its need for available hosts. We found that parasite time to visible infection decreased with increasing temperature at a faster rate than host time to hatching and maturity did, consistent with this hypothesis. We also found that hosts hatched from sexual resting stages are less likely to become infected than those produced clonally and that hosts resistant to many known parasite strains are slower to show signs of visible infection compared to those susceptible to many. Together, these results imply that climate change could lead to earlier seasonal epidemics for this host-parasite system, which may also impact longer-term population dynamics.

opencc-zeroSep 2023View details →

The first arriving virus shapes within-host viral diversity during natural epidemics

Viral diversity has been discovered across scales from host individuals to populations. However, the drivers of viral community assembly are still largely unknown. Within-host viral communities are formed through coinfections, where the interval between the arrival times of viruses may vary. Priority effects describe the timing and order in which species arrive in an environment, and how early colonizers impact subsequent community assembly. To study the effect of the first-arriving virus on subsequent infection patterns of five focal viruses, we set up a field experiment using naïve Plantago lanceolata plants as sentinels during a seasonal virus epidemic. Using joint species distribution modelling, we find both positive and negative effects of early season viral infection on late season viral colonization patterns. The direction of the effect depends on both the host genotype and which virus colonized the host early in the season. It is well-established that co-occurring viruses may change the virulence and transmission of viral infections. However, our results show that priority effects may also play an important, previously unquantified role in viral community assembly. The assessment of these temporal dynamics within a community ecological framework will improve our ability to understand and predict viral diversity in natural systems.

opencc-by-4.0Sep 2023View details →

TranEpiSim: Urban Transportation Epidemic Simulator

This data set is to replicate a case study of disease transmission through micromobility systems and a large synthetic contact network in Cook County.

publicJun 2020View details →

Adaptive changes in the genomes of wild rabbits after 16 years of viral epidemics

Open the record for dataset details and reuse information.