diff --git a/content/english/dashboards/RECOVAC.md b/content/english/dashboards/RECOVAC.md index b8d255f0a..9bb63eb4d 100644 --- a/content/english/dashboards/RECOVAC.md +++ b/content/english/dashboards/RECOVAC.md @@ -9,6 +9,7 @@ menu: identifier: recovac name: Register-based vaccination (RECOVAC) dashboards_topics: [COVID-19, Infectious diseases] +data_status: "updating" # or "historic" --- ## RECOVAC project overview diff --git a/content/english/dashboards/_index.md b/content/english/dashboards/_index.md index 019db0d8c..7b2a7b5e9 100644 --- a/content/english/dashboards/_index.md +++ b/content/english/dashboards/_index.md @@ -3,21 +3,20 @@ title: Dashboards toc: false plotly: true menu: - homepage_dashboards: - name: Dashboards - identifier: dashboards - post: Dashboards are pages describing research done on a given subject. They include visualisations of and links to data from the research groups(s) involved. See all dashboards - dashboard_menu: - identifier: all_dashboards - name: "All dashboards" - weight: 1 + homepage_dashboards: + name: Dashboards + identifier: dashboards + post: Dashboards are pages describing research done on a given subject. They include visualisations of and links to data from the research groups(s) involved. See all dashboards + dashboard_menu: + identifier: all_dashboards + name: "All dashboards" + weight: 1 aliases: - - /dashboards - - /visualisations - - /dashboards_topics/ + - /dashboards + - /visualisations + - /dashboards_topics/ --- -The *Dashboards* section describes research done on a given subject relevant to pandemic preparedness research by researchers affiliated with a Swedish research institute. Specifically, in our case we write about COVID-19 and SARS-CoV-2, infectious diseases in general, antibiotic resistance, enteric viruses and Mpox. The goal is to highlight and visualise openly shared data that can potentially be used by many other researchers to make further discoveries. +Data dashboards are **pages that promote data and other research resources developed by projects involving Swedish researchers or institutes**. The dashboards provide context for the resource, and usually dynamic data visualisations. -To easily find dashboards relevant to a specific topic, simply click on the colored tag and the page will filter and display only the dashboards related to that topic. - \ No newline at end of file +The dashboards are sorted according to when they were last updated, with the most recently updated shown first. All dashboards will be shown by default. Click on **Updating** to view only dashboards where data are still being updated. Click on **Historic** to see dashboards that include only historic data. To see dashboards relevant to a specific **topic**, click on the corresponding coloured topic tag at the bottom of the card (e.g. 'COVID-19', 'Infectious diseases', 'Influenza'). diff --git a/content/english/dashboards/covid_publications.md b/content/english/dashboards/covid_publications.md index e13ca2e5d..ddc7dece0 100644 --- a/content/english/dashboards/covid_publications.md +++ b/content/english/dashboards/covid_publications.md @@ -11,6 +11,7 @@ menu: aliases: - /projects/dashboard/ dashboards_topics: [COVID-19, Infectious diseases] +data_status: "updating" # or "historic" --- The visualisations on this page evaluate the development of COVID-19 and SARS-CoV-2 research across Sweden by assessing publication output. Specifically, we consider multiple aspects of journal publications and preprints where at least one author has an affiliation with a Swedish research institute. The database containing the publications themselves [can be found on this page](/publications/), and is available for download, please see [DOI: 10.17044/scilifelab.14124014](https://doi.org/10.17044/scilifelab.14124014) for details. The database is manually curated, so may not be exhaustive. From May 2023, we began to use the Europe PMC REST API to idenfy publications. The scripts that we use to do this are [openly available on GitHub](https://github.com/ScilifelabDataCentre/pathogens-portal-scripts/tree/main/All_publications) and can be reused for work with other pathogens. The database is updated monthly at the start of the month. diff --git a/content/english/dashboards/crush_covid.md b/content/english/dashboards/crush_covid.md index 303b36f6f..1f3eacf65 100644 --- a/content/english/dashboards/crush_covid.md +++ b/content/english/dashboards/crush_covid.md @@ -11,8 +11,13 @@ menu: aliases: - /data_types/health_data/crush_covid/ dashboards_topics: [COVID-19, Infectious diseases] +data_status: "historic" # or "updating" --- +
+ The data presented here is no longer updated but is kept for historical reference. +
+
@@ -36,7 +41,7 @@ dashboards_topics: [COVID-19, Infectious diseases] #### Download CRUSH Covid data -
Last updated: 2022-09-15
+
Last updated: 2022-09-15 (no longer updating)
- [Number of tests and % positivity by postal code in Uppsala County, .csv file](https://blobserver.dc.scilifelab.se/blob/CRUSH_Covid_data.csv). For each postal code which is found within the Uppsala län, the dataset contains weekly data on cases per capita, tests per capita and % positivity. The estimates are calculated based on the adult population of each postal code (individuals 15 years of age and older). For reference, both the total population and the adult population are included. diff --git a/content/english/dashboards/multidisease_serology.md b/content/english/dashboards/multidisease_serology.md index bc7bb4990..74ed37d2f 100644 --- a/content/english/dashboards/multidisease_serology.md +++ b/content/english/dashboards/multidisease_serology.md @@ -10,8 +10,11 @@ menu: dashboards_topics: [COVID-19, Infectious diseases, Influenza, Enteric viruses, Mpox] toc: true +data_status: "updating" # or "historic" --- +
All data last updated: 2024-08-05
+ ## Introduction The COVID-19 pandemic highlighted the importance of serological surveillance in tracking viral transmission dynamics, understanding immune responses, guiding vaccination strategies, and assisting in decisions related to public health. High-throughput serological assays for SARS-CoV-2 were developed very early in the pandemic at KTH and SciLifeLab to enable surveillance of populations globally. For information about work done with SARS-CoV-2 during the pandemic, see the [historical background section](#historical-background). @@ -376,153 +379,250 @@ The multi-disease serological assay is under constant development and will gradu - - + + + + + - - - - - - - - - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + - - + + + + + diff --git a/content/english/dashboards/npc-statistics.md b/content/english/dashboards/npc-statistics.md index c7146393f..2f404ad08 100644 --- a/content/english/dashboards/npc-statistics.md +++ b/content/english/dashboards/npc-statistics.md @@ -12,9 +12,10 @@ plotly: true aliases: - /data_types/health_data/npc-statistics/ dashboards_topics: [COVID-19, Infectious diseases] +data_status: "historic" # or "updating" --- -
+

The National Pandemic Centre (NPC) at Karolinska Institute ceased operations of high throughput PCR diagnostics on 2020-12-21.

The data presented here is no longer updated but is kept for historical reference.

KI Press Release diff --git a/content/english/dashboards/post_covid.md b/content/english/dashboards/post_covid.md index d9563a569..51a841fe9 100644 --- a/content/english/dashboards/post_covid.md +++ b/content/english/dashboards/post_covid.md @@ -11,8 +11,13 @@ menu: aliases: - /data_types/health_data/post_covid/ dashboards_topics: [COVID-19, Infectious diseases] +data_status: "historic" # or "updating" --- +
+ The data presented here is no longer updated but is kept for historical reference. +
+ Since the beginning of 2020, the COVID-19 pandemic has challenged healthcare and dramatically changed daily life for people worldwide. The severity of symptoms experienced by patients during the acute infection phase of COVID-19 disease varies between individuals from mild to severe. After this phase, there are usually no indications that the disease will have any long-term effects on their health, regardless of the severity of symptoms experienced during the acute infection phase. However, some patients continue to exhibit symptoms for prolonged periods after the acute phase. The symptoms experienced by such patients are broad, but can include, for example, deep fatigue, joint pain, ‘brain fog’ (difficulty concentrating on certain tasks for longer periods of time), and heart palpitations ([Brodin, 2021](https://doi.org/10.1038/s41591-020-01202-8), [Marx, 2021](https://doi.org/10.1038/s41592-021-01145-z)). These symptoms can have a significant impact on the patients' quality of life. Most studies that have explored what causes some patients to experience prolonged symptoms have been descriptive. However, several recent studies have explored potential causes in detail. For example, [Važgėlienė _et al._ (2022)](https://www.mdpi.com/2077-0383/11/21/6278) investigated potential links between prolonged symptoms after COVID-19 infection and other types of chronic disease or daily medication. They found an association between the taking of daily medication and the development of prolonged symptoms after COVID-19 infection. Other studies have found that multiple other factors, including being female, advanced age, and poor general health, are associated with an increased risk of experiencing prolonged symptoms after a COVID-19 infection ([Sudre _et al._, 2021](https://www.nature.com/articles/s41591-021-01292-y)). @@ -27,7 +32,7 @@ For more information on _Post COVID-19 condition_ in Sweden, please see [this se ### Data -
All data last updated: {{% postcovid_date_modified %}}
+
All data last updated: {{% postcovid_date_modified %}} (no longer updating)
The data underlying the visualisations on this page are from [The Swedish Board of Health and Welfare](https://www.socialstyrelsen.se/statistik-och-data/statistik/statistik-om-covid-19/) and comprise of data from both the [Patient Register](https://www.socialstyrelsen.se/statistik-och-data/register/alla-register/patientregistret/) and the [‘Cause of Death’ Register](https://www.socialstyrelsen.se/statistik-och-data/register/alla-register/dodsorsaksregistret/). The data are updated monthly, on the second Wednesday of the month, and are available for download [here](https://www.socialstyrelsen.se/statistik-och-data/statistik/statistik-om-covid-19/). Additional data about COVID-19 can be requested from the corresponding registers by any researchers fulfilling the requirements for access, the guidelines for access via the RUT (Register Utiliser Tool) are available [here](https://bestalladata.socialstyrelsen.se/data-for-forskning/). diff --git a/content/english/dashboards/serology-statistics.md b/content/english/dashboards/serology-statistics.md index 1c54cbe35..705cd01ed 100644 --- a/content/english/dashboards/serology-statistics.md +++ b/content/english/dashboards/serology-statistics.md @@ -15,6 +15,7 @@ aliases: - /data_types/health_data/serology-statistics/ dashboards_topics: [COVID-19, Infectious diseases] plotly: true +data_status: "updating" # or "historic" ---
@@ -28,7 +29,7 @@ Serology tests involve testing bodily fluids for the presence of antibodies or o - **Negative tests**: Serology tests indicating the _absence_ of immunoglobulin G (IgG) antibodies targeting SARS-CoV-2 proteins. - **R&D tests**: All of the remaining serum, plasma, and saliva samples that were completed to test the levels IgG, IgM, or IgA antibodies targeting SARS-CoV-2 proteins. This includes all of the positive and negative controls, all replicated and re-ran samples and assays, all samples analysed during the continuous development and optimisation of the tests, technically failed samples, and all research associated projects. -
Data last updated: {{% serology_date_modified %}}.
+
Data last updated: {{% serology_date_modified %}}
## Weekly serology tests diff --git a/content/english/dashboards/symptom_study_sweden.md b/content/english/dashboards/symptom_study_sweden.md index 70f4fcb7f..9298e9051 100644 --- a/content/english/dashboards/symptom_study_sweden.md +++ b/content/english/dashboards/symptom_study_sweden.md @@ -12,8 +12,13 @@ menu: aliases: - /data_types/health_data/symptom_study_sweden/ dashboards_topics: [COVID-19, Infectious diseases] +data_status: "historic" # or "updating" --- +
+ The data presented here is no longer updated but is kept for historical reference. +
+ **COVID Symptom Study Sweden** is a national research initiative for large-scale data collection and analysis of symptoms, exposure, and risk factors associated with the COVID-19 infection. The project is run by Lund University and Uppsala University in collaboration with King’s College London and Zoe Global Ltd. COVID Symptom Study Sweden is led by prof. Paul Franks and prof. Maria Gomez (Lund University) as well as prof. Tove Fall (Uppsala University). [COVID Symptom Study Sweden](https://www.covid19app.lu.se/) uses a non-commercial app for data collection from volunteer study participants. Anyone 18 years or older living in Sweden can participate in the study. As of March 2021, COVID Symptom Study Sweden has over 206,000 participants and accumulated over 12 million data points. @@ -22,7 +27,7 @@ COVID Symptom Study Sweden has two main objectives. The first objective is to in #### Estimated prevalence of symptomatic cases -
Last updated: {{% csss_date_modified %}}.
+
Last updated: {{% csss_date_modified %}} (no longer updating)
Below are estimates of the prevalence of symptomatic COVID-19 cases in various counties in Sweden. The estimates are made based on the app users' data using the prediction model developed by the team of researchers behind the COVID Symptoms Study Sweden; see [this page](https://www.covid19app.lu.se/artikel/uppdatering-av-prediktionsmodell-0) for more information about the prediction model (only available in Swedish). More detailed prevalence estimates and other results can be explored [on the official dashboard of the project results](https://csss-resultat.shinyapps.io/csss_dashboard/). diff --git a/content/english/dashboards/vaccines.md b/content/english/dashboards/vaccines.md index 0e36907ca..62ecd063e 100644 --- a/content/english/dashboards/vaccines.md +++ b/content/english/dashboards/vaccines.md @@ -11,6 +11,7 @@ menu: aliases: - /data_types/health_data/vaccines/ dashboards_topics: [COVID-19, Infectious diseases] +data_status: "historic" # or "updating" ---
@@ -47,11 +48,11 @@ For more information on vaccination in Sweden, please also see the [RECOVAC dash ## Visualisations related to vaccination coverage -
The visualisations on this page were last updated: 2023-03-24.
+
The visualisations on this page were last updated: 2023-03-24 (no longer updating)
-The [Swedish Health Agency (Folkhälsomyndigheten, FoHM)](https://folkhalsomyndigheten.se) provide information, summary statistics, and data related to COVID-19 vaccination in Sweden [(only available in Swedish)](https://www.folkhalsomyndigheten.se/folkhalsorapportering-statistik/statistikdatabaser-och-visualisering/vaccinationsstatistik/statistik-for-vaccination-mot-covid-19/). The visualisations below are based on the publicly available COVID-19 vaccination data from FoHM, which can be [downloaded directly](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data). For each visualisation, we describe which data in the dataset were used, how calculations were completed, and provide a link to the script(s) used to produce it. +The [Swedish Health Agency (Folkhälsomyndigheten, FoHM)](https://folkhalsomyndigheten.se) provide information, summary statistics, and data related to COVID-19 vaccination in Sweden [(only available in Swedish)](https://www.folkhalsomyndigheten.se/folkhalsorapportering-statistik/statistikdatabaser-och-visualisering/vaccinationsstatistik/statistik-for-vaccination-mot-covid-19/). The visualisations below are based on the publicly available COVID-19 vaccination data from FoHM, which can be [downloaded directly](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx). For each visualisation, we describe which data in the dataset were used, how calculations were completed, and provide a link to the script(s) used to produce it. -The source data is updated weekly (on Thursdays), and the visualisations on this page will be updated shortly thereafter (usually on Fridays). All of our code related to this page is available on [GitHub](https://github.com/ScilifelabDataCentre/pathogens-portal-visualisations/tree/main/Vaccine_page). All of the vaccine data is processed using a single [data preparation script](https://github.com/ScilifelabDataCentre/pathogens-portal-visualisations/blob/main/Vaccine_page/vaccine_dataprep_Swedentots.py). The code required to generate each visualisation/number set is linked close to the corresponding plot/text. + All of our code related to this page is available on [GitHub](https://github.com/ScilifelabDataCentre/pathogens-portal-visualisations/tree/main/Vaccine_page). All of the vaccine data is processed using a single [data preparation script](https://github.com/ScilifelabDataCentre/pathogens-portal-visualisations/blob/main/Vaccine_page/vaccine_dataprep_Swedentots.py). The code required to generate each visualisation/number set is linked close to the corresponding plot/text. ### General summary statistics @@ -65,7 +66,7 @@ In the chart below, we show vaccine coverage as calculated using the 'whole popu Please note, we refer to the number of doses administered (at least) for simplicity. However, other sources may use specific names/classifications to refer to different doses. For example, individuals given at least 2 doses may be considered 'fully vaccinated'. The third dose is also sometimes referred to as a 'booster dose'. Individuals with at least 3 doses are thus sometimes said to be 'fully vaccinated with a booster dose'. Other variations also exist, and other terms may arise as subsequent doses becomes more widely available. -Vaccination data is spread between multiple tabs of the [FoHM data file](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data). For calculations done using the 'eligible population method', we used percentage data from the 'Vaccinerade tidsserie', 'Vaccinerade tidsserie dos 3', 'Vaccinerade tidsserie dos 4', and 'Vaccinerade tidsserie dos 5' tabs of the [FoHM data file](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data). These tabs contained data about the amount of individuals that received at least one or two doses, at least 3 doses, at least 4 doses, and at least 5 doses, respectively. For the 'whole population method', we use the latest population data from [Statistics Sweden (SCB)](https://www.scb.se/) and the most recent 'raw number' of the doses administered from same tabs in the [FoHM data file](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data). +Vaccination data is spread between multiple tabs of the [FoHM data file](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx). For calculations done using the 'eligible population method', we used percentage data from the 'Vaccinerade tidsserie', 'Vaccinerade tidsserie dos 3', 'Vaccinerade tidsserie dos 4', and 'Vaccinerade tidsserie dos 5' tabs of the [FoHM data file](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx). These tabs contained data about the amount of individuals that received at least one or two doses, at least 3 doses, at least 4 doses, and at least 5 doses, respectively. For the 'whole population method', we use the latest population data from [Statistics Sweden (SCB)](https://www.scb.se/) and the most recent 'raw number' of the doses administered from same tabs in the [FoHM data file](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx). **Note on the graph:** Click on the coloured squares in the legend of the below graph to toggle which datasets are displayed. A single click will toggle just that dataset on/off. It is possible to display only one of the datasets by double-clicking on the desired dataset. @@ -83,7 +84,7 @@ To summarise, in total, % of the population In Sweden, the first vaccine doses were administered in early 2021. As in other countries, the first two doses were made available to progressively younger age groups over time. The third dose of the vaccine was first offered in autumn of 2021, and was offered to individuals in particular ages groups at a given interval after their second dose. The age group and interval length differed over time, with age groups generally getting younger and the interval becoming shorter. A third dose is not offered to those under 18 years of age, unless there are additional considerations e.g. the individual is immunocompromised. In early 2022, a fourth dose was made available to those aged over 80, those receiving care, those living in housing facilities for the elderly, and those with severe immunodeficiency. This was extended to include those over 65 in April 2022. As of September 2022, it was made largely available to those over 18, though the availability varied between counties. At each stage of the rollout of the fourth dose, exceptions were made so that others could get the fourth dose under specific circumstances, for example, where an individual is immunocompromised or taking care of a vulnerable individual. A fifth dose was made available to those over 65 in September 2022 and, as with the other doses, it is likely to be made available to more of the population over time and other groups are able to access it under certain conditions. -Time series data is available in different tabs of the [FoHM data file](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data). We therefore took data from different places to produce the below time series. Time series data related to the amount of individuals that have received at least one or two doses is available in the 'Vaccinerade tidsserie' tab. Time series data about the amount of individuals that have at least 3, 4, or 5 doses is available in the 'Vaccinerade tidsserie dos 3', 'Vaccinerade tidsserie dos 4', and 'Vaccinerade tidsserie dos 5' tabs, respectively. Again, please note that it would not be appropriate to compare across all of the dose levels, both because the vaccines are not similarly available and because FoHM do not include all of the doses administered in their data. Firstly, a dose is only 'counted' in the FoHM data if it is administered to an individual within a specific age range. Data on the first on second doses is only included for individuals born in or before 2010 (around 12 years old). Data on the third and fourth doses is only included for individuals born in or before 2004 (around 18 years old). Data on the fifth dose is only included if it was given to an individual born in or before 1957 (around 65 years old). There are also some other caveats about whether a dose is 'counted' in the data file. In particular, data on the third dose is only included if it was registered after 1st September 2021 and at least 8 weeks after the individual received their second dose. Similarly, data on the fourth dose is only included if it was registered after 21st January 2022 and at least 8 weeks after the individual received their third dose. Lastly, data on dose 5 is only included if the dose was registerd after 15th August 2022 and was received at least 80 days after the individual received dose 4. +Time series data is available in different tabs of the [FoHM data file](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx). We therefore took data from different places to produce the below time series. Time series data related to the amount of individuals that have received at least one or two doses is available in the 'Vaccinerade tidsserie' tab. Time series data about the amount of individuals that have at least 3, 4, or 5 doses is available in the 'Vaccinerade tidsserie dos 3', 'Vaccinerade tidsserie dos 4', and 'Vaccinerade tidsserie dos 5' tabs, respectively. Again, please note that it would not be appropriate to compare across all of the dose levels, both because the vaccines are not similarly available and because FoHM do not include all of the doses administered in their data. Firstly, a dose is only 'counted' in the FoHM data if it is administered to an individual within a specific age range. Data on the first on second doses is only included for individuals born in or before 2010 (around 12 years old). Data on the third and fourth doses is only included for individuals born in or before 2004 (around 18 years old). Data on the fifth dose is only included if it was given to an individual born in or before 1957 (around 65 years old). There are also some other caveats about whether a dose is 'counted' in the data file. In particular, data on the third dose is only included if it was registered after 1st September 2021 and at least 8 weeks after the individual received their second dose. Similarly, data on the fourth dose is only included if it was registered after 21st January 2022 and at least 8 weeks after the individual received their third dose. Lastly, data on dose 5 is only included if the dose was registerd after 15th August 2022 and was received at least 80 days after the individual received dose 4. The below graph shows vaccine coverage across the whole of Sweden. We use the 'whole population' method for calculation, as this is more often used by other countries. Our calculations will therefore differ from the percentage values provided by FoHM as part of their summary statistics, because they use the 'eligible population' method of calculation. For more details on the two methods, see the [general summary statistics](/dashboards/vaccines/#general-summary-statistics) section. @@ -97,7 +98,7 @@ The below graph shows vaccine coverage across the whole of Sweden. We use the 'w ### Administration of vaccinations in each Swedish county (län) -In this section, we explore how many individuals in a given Swedish county (län) had at least X vaccine doses. Here, we again use the 'whole population' method of calculation (see the [general summary statistics](/dashboards/vaccines/#general-summary-statistics) section for details). Data on the total number of people in each county was taken from [Statistics Sweden (SCB)](https://www.scb.se/en/finding-statistics/statistics-by-subject-area/population/population-composition/population-statistics/). Data on the amount of individuals given at least one or two doses in each county was taken from the 'Vaccinerade tidsserie' tab of the [data from FoHM](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data). As mentioned in previous sections, only doses given to individuals born in or before 2010 (around 12 years old) are counted. Data on the amount of individuals given at least 3 or 4 doses (available in the 'Vaccinerade tidsserie dos 3' and 'Vaccinerade tidsserie dos 4' tabs of the [FoHM data](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data), respectively) is only given for those born bore 2004 (around 18 years old) and in accordance with specific timeframes and registration timepoints. Data on the fifth dose (available in the 'Vaccinerade tidsserie dos 5' tab of the [FoHM data](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data)) is only available for those born before 1957 (around 65 years old), and in accordance with certain timeframes. Given the differences in which data is 'counted' for each dose, it is clear that data should not be compared across doses. +In this section, we explore how many individuals in a given Swedish county (län) had at least X vaccine doses. Here, we again use the 'whole population' method of calculation (see the [general summary statistics](/dashboards/vaccines/#general-summary-statistics) section for details). Data on the total number of people in each county was taken from [Statistics Sweden (SCB)](https://www.scb.se/en/finding-statistics/statistics-by-subject-area/population/population-composition/population-statistics/). Data on the amount of individuals given at least one or two doses in each county was taken from the 'Vaccinerade tidsserie' tab of the [data from FoHM](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx). As mentioned in previous sections, only doses given to individuals born in or before 2010 (around 12 years old) are counted. Data on the amount of individuals given at least 3 or 4 doses (available in the 'Vaccinerade tidsserie dos 3' and 'Vaccinerade tidsserie dos 4' tabs of the [FoHM data](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx), respectively) is only given for those born before 2004 (around 18 years old) and in accordance with specific timeframes and registration timepoints. Data on the fifth dose (available in the 'Vaccinerade tidsserie dos 5' tab of the [FoHM data](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx)) is only available for those born before 1957 (around 65 years old), and in accordance with certain timeframes. Given the differences in which data is 'counted' for each dose, it is clear that data should not be compared across doses. As data for the fifth dose is available to such a small amount of the population, we have decided to analyse the data using both the 'whole population' and 'eligible population' methods. We feel that this will allow a clearer understanding of the differences between län in terms of the coverage for the fourth dose. @@ -154,7 +155,7 @@ Please note the differences between the two below maps. Coverage appears to be v The below heatmap provides some indication of the vaccine coverage across different age groups. The data for this **heatmap differs from that in the previous visualisations**. Specifically, instead of showing the number of people with 'at least X doses', the heatmap shows the number of people in Sweden in each age group that have been given **that specific number of doses**. For example, rather than showing the amount of people with 'at least one dose', we show the number that have had 'only one dose'. Understandably, the number that have received ONLY one dose is relatively low across all age groups; individuals that have taken one dose are naturally more likely to take subsequent doses when they become eligible to do so. Given that individuals in more advanced age categories are eligible to take more doses, coverage is likely to be higher at a greater dose level. Age groups that have only recently become eligible for a given dose level are likely to initially show low coverage. -The fact that data is not available for each age category for every dose is reflected in the graph (a white colouration is used to indicate where data is not available/included). Data on the first three doses are available in the 'Dos 1 till 3 per åldersgrupp' tab of the [FoHM dataset](https://fohm.maps.arcgis.com/sharing/rest/content/items/fc749115877443d29c2a49ea9eca77e9/data)). Data on the fourth and fifth doses are instead available in the 'Dos 4 18+' and 'Dos 5 per åldersgrupp' tabs, respectively. +The fact that data is not available for each age category for every dose is reflected in the graph (a white colouration is used to indicate where data is not available/included). Data on the first three doses are available in the 'Dos 1 till 3 per åldersgrupp' tab of the [FoHM dataset](https://blobserver.dc.scilifelab.se/blob/Folkhalsomyndigheten_Covid19_Vaccine-93.xlsx). Data on the fourth and fifth doses are instead available in the 'Dos 4 18+' and 'Dos 5 per åldersgrupp' tabs, respectively. The 'eligible population method' was used in this case, as it would not be appropriate to consider the whole population when considering vaccination coverage within specific age groups. diff --git a/content/english/dashboards/variants_region_uppsala.md b/content/english/dashboards/variants_region_uppsala.md index ee7260f40..f5c6ae9a0 100644 --- a/content/english/dashboards/variants_region_uppsala.md +++ b/content/english/dashboards/variants_region_uppsala.md @@ -9,6 +9,7 @@ menu: identifier: clinmicro_uppsala name: SARS-CoV-2 whole genome sequencing (Region Uppsala) dashboards_topics: [COVID-19, Infectious diseases] +data_status: "updating" # or "historic" --- ## Introduction diff --git a/content/english/dashboards/wastewater/_index.md b/content/english/dashboards/wastewater/_index.md index e8c42d0f5..bcc6fa67c 100644 --- a/content/english/dashboards/wastewater/_index.md +++ b/content/english/dashboards/wastewater/_index.md @@ -21,6 +21,7 @@ aliases: - /data_types/environment/ - /dashboards/wastewater/introduction/ dashboards_topics: [COVID-19, Infectious diseases, Enteric viruses, Influenza] +data_status: "updating" # or "historic" --- ## Introduction diff --git a/content/english/dashboards/wastewater/covid_quantification/covid_quant_GU.md b/content/english/dashboards/wastewater/covid_quantification/covid_quant_GU.md index 7ffbd9b47..636cf4737 100644 --- a/content/english/dashboards/wastewater/covid_quantification/covid_quant_GU.md +++ b/content/english/dashboards/wastewater/covid_quantification/covid_quant_GU.md @@ -10,11 +10,13 @@ aliases:

+
As of April 2024, the SARS-CoV-2 data will no longer be updated by GU. Data from after April 2024 is available from other research groups.
+ ## Introduction This project is led by Professor Helene Norder (University of Gothenburg, GU), and supported by co-workers from the University of Gothenburg and Sahlgrenska University Hospital (Hao Wang, Marianela Patzi Churqui, Timur Tunovic, Fredy Saguti, and Kristina Nyström). The wastewater sample collections were performed by Lucica Enache at Ryaverket, Gryaab AB, Gothenburg. -The group began collecting samples on 10th February (week 7) 2020. They updated the methods related to analysing the samples during 2023, and began to use this updated method on 15th May (week 20) 2023. This page concerns only the data collected using their updated method. The associated data and visualisation are **updated approximately weekly**. Corresponding information about data collected using an earlier method is available in the ['Historic SARS-CoV-2 data from Gothenburg' page](/dashboards/wastewater/covid_quantification/historic_covid_gu/). +The group began collecting samples on 10th February (week 7) 2020. They updated the methods related to analysing the samples during 2023, and began to use this updated method on 15th May (week 20) 2023. This page concerns only the data collected using their updated method. The associated data and visualisation are **no longer being updated**. Corresponding information about data collected using an earlier method is available in the ['Historic SARS-CoV-2 data from Gothenburg' page](/dashboards/wastewater/covid_quantification/historic_covid_gu/). The SARS-CoV-2 virus monitoring by the Norder group was done alongside their ongoing monitoring of enteric viruses in wastewater, the data for which are [also shared on this portal](/dashboards/wastewater/enteric_quantification/). @@ -24,7 +26,7 @@ Influent wastewater samples were collected from Ryaverket wastewater treatment p ## Visualisation -
Last updated:
+
Last updated: (no longer updating)
Rotating your phone may improve graph layout diff --git a/content/english/dashboards/wastewater/covid_quantification/covid_quant_KTH.md b/content/english/dashboards/wastewater/covid_quantification/covid_quant_KTH.md index 7a9fcdb9b..0936f7c5d 100644 --- a/content/english/dashboards/wastewater/covid_quantification/covid_quant_KTH.md +++ b/content/english/dashboards/wastewater/covid_quantification/covid_quant_KTH.md @@ -5,18 +5,18 @@ aliases: - /dashboards/wastewater/covid_quant_kth/ --- -
As of June 2023, the SARS-CoV-2 data will no longer be updated by SEEC-KTH. Data from after June 2023 is available from other research groups.
-
Go back to SARS-CoV-2 quantification within the wastewater epidemiology dashboard

+
As of June 2023, the SARS-CoV-2 data will no longer be updated by SEEC-KTH. Data from after June 2023 is available from other research groups.
+ ## Introduction This project is led by associate professor Zeynep Cetecioglu Gurol and supported by Mariel Perez-Zabaleta and Isaac Owusu-Agyeman at KTH Royal Institute of Technology (KTH). Bioinformatics analyses of wastewater samples are held by assistant professor Luisa Hugerth (Uppsala University). This group of researchers are known as SEEC-KTH. The project was established as a collaboration between the [SciLifeLab COVID-19 National Research Program](https://www.scilifelab.se/covid-19), and the [SEED](https://www.kth.se/en/seed) and [Chemical Engineering](https://www.kth.se/ket/chemical-engineering-1.784196) departments at KTH. The project is now funded as part of the SciLifeLab Pandemic Laboratory Preparedness (PLP) Program. More information about the PLP program can be found in our [resources section](/resources/). SEEC-KTH is now part of the [Department of Industrial Biotechnology](https://www.kth.se/dib/department-of-industrial-biotechnology-1.783103) at KTH. -The data and visualisations on this page are usually updated weekly, typically on Fridays. Data and information about the group on this dashboard are updated frequently, so please check back regularly to stay up to date. +The data and visualisations on this page are **no longer being updated**. ## Wastewater collection sites @@ -34,7 +34,7 @@ Please also note that although the same methods are used for all cities shown on ### Stockholm -
Last updated:
+
Last updated: (no longer updating)
{{ end }} diff --git a/layouts/partials/dashboards.html b/layouts/partials/dashboards.html index 6c6e546ad..11a2c03bd 100644 --- a/layouts/partials/dashboards.html +++ b/layouts/partials/dashboards.html @@ -1,50 +1,232 @@ {{ $dashboards := .Site.Menus.dashboard_menu }} {{ $currentPage := path.Split (path.Clean .RelPermalink) }} -{{ $homepage_dashboards := slice "clinmicro_uppsala" "post_covid" "wastewater" }} {{ $displayed_in_homepage := .IsHome }} {{ $dashboards_to_show := slice }} -{{/* Compile list of highlight to show depending upon the page */}} -{{ if eq $currentPage.File "dashboards" }} +{{/* Compile list of dashboards to show depending upon the page */}} +{{ if or (eq $currentPage.File "dashboards") ($displayed_in_homepage) }} {{ $dashboards_to_show = $dashboards_to_show | append (where $dashboards "Identifier" "ne" "all_dashboards") }} -{{ else if $displayed_in_homepage }} - {{ $dashboards_to_show = $dashboards_to_show | append (where $dashboards "Identifier" "in" $homepage_dashboards) }} {{ else if strings.HasSuffix $currentPage.Dir "/topics/" }} {{ range $dashboards }} {{if in (apply .Page.Params.dashboards_topics "urlize" ".") $currentPage.File }} {{ $dashboards_to_show = $dashboards_to_show | append . }} {{ end }} {{ end }} - {{ if strings.HasPrefix $currentPage.Dir "/topics/" }} - {{ $dashboards_to_show = first 3 $dashboards_to_show }} - {{ end }} {{ end }} -
- {{ range $dashboards_to_show }} -
-
- - -
-
{{ .Name }}
-
-
- {{ .Page.Description }} -
- {{ if not $displayed_in_homepage }} -
- {{ range (.Page.GetTerms "dashboards_topics") }} - {{ .LinkTitle }} - {{ end }} + + +
+ + {{ if or (eq $currentPage.File "dashboards") (strings.HasSuffix $currentPage.Dir "/dashboards/topics/" ) }} + + - {{ end }} +
+ {{ end }} + +
+
+ {{ range $dashboards_to_show }} + {{ $dashboardPage := path.Split (path.Clean .Page.RelPermalink) }} +
+
+ + +
+
{{ .Name }}
+
+
+ Updated: +
+
+ {{ .Page.Description }} +
+ {{ if not $displayed_in_homepage }} +
+ {{ range (.Page.GetTerms "dashboards_topics") }} + {{ .LinkTitle }} + {{ end }} +
+ {{ end }} +
+
+ {{ end }} +
+
+
+ + +{{ if or (eq $currentPage.File "dashboards") (strings.HasSuffix $currentPage.Dir "/dashboards/topics/" ) }} + +{{ end }} + + + diff --git a/layouts/partials/navbar.html b/layouts/partials/navbar.html index 678b95715..d5180f3b5 100644 --- a/layouts/partials/navbar.html +++ b/layouts/partials/navbar.html @@ -105,22 +105,22 @@
- -
- -
GroupSubtype/Linage/StrainVirus TypeVariantProteinDetailsHost
PertussisBordetella pertussis Filamentous Hemagglutinin (FHA)
PertussisBordetella pertussis Filamentous Hemagglutinin (FHA) - Bulk antigen
PertussisB. Pertussis toxin (mutant)Bordetella PertussisFilamentous haemagglutinin
PertussisB. Pertussis Pertactin Protein [His]Bordetella PertussisPertussis toxinNative
PertussisBordetella pertussis Filamentous Hemagglutinin (FHA) - NativeantigenBordetella PertussisMembrane protein PertactinE. coli
PertussisB. Pertussis whole-cell (strain tahoma I)Bordetella PertussisStrain Tomaha IFilamentous haemagglutininNative
MeaslesMeasles Virus Nucleoprotein (HEK293)Bordetella PertussisStrain Tomaha INative protein, whole cell
MeaslesNative Measles virusClostridium TetanisTetanus toxinHeavy chain fragment C
RotavirusRotavirus VP7 ProteinClostridium TetanisTetanus toxoidNative
RotavirusRotaVirus (Strain SA-11)Corynebacterium DiphteriaDiphtheria toxinMutated G52E, native full length
RubellaRubella virus nucleoprotein, C-terminal His-tagCorynebacterium DiphteriaStrain NCTC 10648
RubellaRubella Virus Grade 4, natural antigen.CytomegalovirusGlycoprotein BHEK
RubellaRubella E1Epstein Barr VirusGlycoprotein 125HEK
RubellaRubella virus E1, C-terminal SHFC-tagHepatitis VirusHBVSurface antigen, subtype adwP. pastoris
RubellaRubella Spike Ectodomain (E1-E2)Human Papillomavirus (HPV)Type 16Capsid protein L1Full lengthYeast
DiphtheriaDiphtheria mutated toxinHuman Papillomavirus (HPV)Type 18Capsid protein L1Full lengthS. cerevisae
DiphtheriaDiphtheria ToxoidHuman Papillomavirus (HPV)Type 6Capsid protein L1E. coli
MumpsMumps Virus Nucleoprotein RecombinantHuman Papillomavirus (HPV)Type 33Capsid protein L1E. coli
MumpsMumps virus nucleoproteinMeasles VirusNucleoproteinHEK
MumpsMumps virus nucleoprotein, inactivated pathogen.Measles VirusStrain EdmonstonNativeVero cells
MumpsNative Mumps virusMumps VirusNucleoproteinE. coli
Humant PapillomvirusHPV type 16 L1 Protein (full length)Mumps VirusStrain Jeryl-LynnNucleoproteinFull lengthHEK
Humant PapillomvirusHPV type 18 L1 Protein (full length)Mumps VirusNucleoprotein
Humant PapillomvirusRecombinant HPV type 6 L1 protein (VLP)Mumps VirusStrain EndersNativeBSC-1 cells
Humant PapillomvirusRecombinant Human Papilloma Virus type 33 L1 protein (VLP)PoliovirusType 1, Strain SabinCapsid proteinE. coli
PneumococcusS. Pneumoniae Cell Wall Polysaccharide AntigenPoliovirusType 2Capsid protein VP3-VP1E. coli
TetanusClostridium tetani Tetanus ToxoidPoliovirusType 3Capsid protein VP3-VP1E. coli
TetanusTetanus Toxoid, Recombinant Heavy Chain Fragment CRespiratory Syncytial Virus (RSV)RSVAGlycoprotein GHEK
Hepatit-BHBV Surface Antigen (subtype adw)RotavirusStrain Rotavirus A/RVA/Vaccine/USA/Rotarix-AROLA490AB/1988/G1P1AGlycoprotein VP7HEK
Poliovirus Recombinant Poliovirus type 1 Capsid protein (strain Sabin)RotavirusStrain SA-11MA 104 cells
Poliovirus Recombinant Poliovirus type 2 VP3-VP1 capsid Protein [His]Rubella VirusGrade 4 antigen
Poliovirus Recombinant Poliovirus type 3 VP3-VP1 capsid proteinRubella VirusStrain F-TherienNucleoproteinHEK
Cytomegalovirus (CMV)Cytomegalovirus glycoprotein B (gB)Rubella VirusGlycoprotein E1E. coli
Epstein–Barr virus (EBV)Epstein Barr Virus gp125Rubella VirusStrain F-TherienSpike glycoprotein E1HEK
Epstein–Barr virus (EBV)Epstein–Barr nuclear antigen 1Rubella VirusStrain HPV-77Spike glycoprotein E1 & E2Rubella VaccineInsect cells
Respiratory syncytialRespiratory Syncytial Virus A Glycoprotein GStreptococcus PneumoniaeCell wall polysaccharide antigenNative