Package 'rsurvstat'

SurvStat age group list

Description

• single_year

• children_coarse: from 0, 15, 20, 25, 30, 40, 50, 60, 70, 80 years

• children_medium: from 0, 5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80 years

• children_fine: from 0, 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80 years

• five_year: from 0, 1, 5, 10, 15, 20, … , 75, 80 years

• zero_fifteen: from 0, 15+ years

• zero_fifteen_sixty: from 0, 15, 60+ years

• zero_one_4_20_40_60_80: from 0, 4, 20, 40, 60, 80+ years

Usage

age_groups

Format

An object of class list of length 8.

References

https://survstat.rki.de/Content/Query/Create.aspx

---

A Berlin outline sf map

Description

A Berlin outline sf map

Usage

data(BerlinMap)

Format

A sf dataframe containing the following columns:

• Name (character) - the Name column

1 rows

---

Delete all cached SurvStat requests

Description

This function is only intended to be used interactively. The cache can be controlled with set_cache_settings()

Usage

cache_clear(confirm = utils::askYesNo("Are you sure?"))

Arguments

confirm

can be set to TRUE to make function non interactive.

Value

nothing. called for side effects

Examples

cache_clear( confirm = interactive() )

---

The CountyKey71Map dataset

Description

This matches the CountyKey71 dimension in SurvStat. This is the 400 Stadtkreis and Landkreise administrative regions in Germany, plus 12 Berlin boroughs (Bezirke) which replace the Berlin Kriese (Id: 11000). The boroughs have sequential Ids from ⁠[11001]⁠ to ⁠[11012]⁠

Usage

data(CountyKey71Map)

Format

A sf dataframe containing the following columns:

• Id - the full SurvStat identifier for this region (includes hierarchical information)

• ComponentId - the id of the most granular geographical unit (which can be used to link out to other data sets)

• HierarchyId - the id of the geographical unit type

• Name - the name of the region

Any grouping allowed.

411 rows

---

SurvStat disease list

Description

Supported diseases:

• Acinetobacter (key: Acinetobacter-Infektion oder –Kolonisation)

• Adenovirus (key: Adenovirus (andere Form, Meldepflichtig gemäß Landesmeldeverordnung))

• Amoebiasis (key: Amoebiasis)

• Anthrax (key: Milzbrand)

• Arbovirus (key: Arbovirus-Erkrankung)

• Astrovirus (key: Astrovirus-Infektion)

• Bornavirus (key: Bornavirus)

• Botulism (key: Botulismus)

• Brucellosis (key: Brucellose)

• CJD (key: CJK)

• CJD, variant (key: vCJK)

• COVID-19 (key: COVID-19)

• Campylobacter (key: Campylobacter-Enteritis)

• Candida auris (invasive) (key: Candida auris, invasive Infektion)

• Chickenpox (key: Windpocken)

• Chickenpox (state) (key: Windpocken (Meldepflicht gemäß Landesmeldeverordnung))

• Chickungunya (key: Chikungunya-Fieber)

• Chlamydia Trachomatis (key: Chlamydia-trachomatis-Infektion)

• Cholera (key: Cholera)

• Clostridium difficile / mild (key: Clostridium difficile, nicht schwerer Verlauf)

• Clostridium difficile / moderate (key: Clostridium difficile, schwerer Verlauf)

• Cryptosporidiosis (key: Kryptosporidiose)

• Cytomegalovirus (key: Cytomegalie)

• Dengue (key: Denguefieber)

• Diptheria (key: Diphtherie)

• E. Coli, enteritis (key: E.-coli-Enteritis)

• E. Coli, enterohemorrhagic (key: EHEC-Erkrankung)

• Ebola (key: Ebolafieber)

• Echinococcosis (key: Echinokokkose)

• Enterobacteria colonisation (key: Enterobacteriaceae-Infektion oder –Kolonisation)

• Enterovirus (key: Enterovirus)

• Gas gangrene (key: Gasbrand)

• Gastroenteritis (other) (key: Weitere bedrohliche Krankheit (gastro))

• Giardia (key: Giardiasis)

• Gonorrhoea (key: Gonorrhoe)

• Group B Streptococcus (key: Gruppe-B-Streptokokken)

• HIV (key: HIV-Infektion)

• Haemolytic-uraemic syndrome (key: HUS (Hämolytisch-urämisches Syndrom), enteropathisch)

• Haemophilus influenza, invasive (key: Haemophilus influenzae, invasive Erkrankung)

• Hand foot mouth disease (key: Hand-Fuß-Mund-Krankheit)

• Hantavirus (key: Hantavirus-Erkrankung)

• Head lice (key: Kopflausbefall)

• Hepatitis (general) (key: Hepatitis (allgemein))

• Hepatitis A (key: Hepatitis A)

• Hepatitis B (key: Hepatitis B)

• Hepatitis C (key: Hepatitis C)

• Hepatitis D (key: Hepatitis D)

• Hepatitis E (key: Hepatitis E)

• Hepatitis non A-E (key: Hepatitis Non A-E)

• Herpes Zoster (key: Herpes Zoster)

• Influenza, seasonal (key: Influenza, saisonal)

• Influenza, zoonotic (key: Influenza, zoonotisch)

• Keratoconjunctivitis (IfSG) (key: Keratokunjunktivitis (Meldepflicht gemäß IfSG))

• Keratoconjunctivitis (state) (key: Keratokunjunktivitis (Meldepflicht gemäß Landesmeldeverordnung))

• Lassa fever (key: Lassafieber)

• Legionalla (key: Legionellose)

• Leprousy (key: Lepra)

• Leptospirosis (key: Leptospirose)

• Listeriosis (key: Listeriose)

• Lyme Disease (key: Borreliose)

• MERS (key: Middle East Respiratory Syndrome)

• MRSA, invasive (key: MRSA, invasive Infektion)

• Malaria (IfSG) (key: Malaria (§7(3) IfSG))

• Malaria (state) (key: Malaria, Länderverordnung)

• Marburg virus (key: Marburgfieber)

• Measles (key: Masern)

• Meningitis (other) (key: Meningitis, andere)

• Meningococcal, invasive (key: Meningokokken, invasive Erkrankung)

• Mpox (key: Affenpocken)

• Mpox (key: Affenpocken)

• Mumps (IfSG) (key: Mumps (Meldepflicht gemäß IfSG))

• Mumps (state) (key: Mumps (Meldepflicht gemäß Landesmeldeverordnung))

• Mycoplasma (key: Mycoplasma)

• Norovirus (key: Norovirus-Gastroenteritis)

• Orthinovirus (key: Ornithose)

• Orthopox (key: Orthopocken)

• Parainfluenze (key: Parainfluenza)

• Paratyphus (key: Paratyphus)

• Plague (key: Pest)

• Pneumococcus (IfSG) (key: Pneumokokken (Meldepflicht gemäß IfSG))

• Pneumococcus (state) (key: Pneumokokken (Meldepflicht gemäß Landesverordnung))

• Poliomyelitis (key: Poliomyelitis)

• Q-fever (key: Q-Fieber)

• RSV (IfSG) (key: RSV (Meldepflicht gemäß IfSG))

• RSV (state) (key: RSV (Meldepflicht gemäß Landesmeldeverordnung))

• Rabies (confirmed) (key: Tollwut)

• Rabies (suspected) (key: Tollwutexpositionsverdacht)

• Relapsing fever (key: Läuserückfallfieber)

• Ringworm (key: Ringelröteln)

• Rotavirus gastroenteritis (key: Rotavirus-Gastroenteritis)

• Rubella (key: Röteln, postnatal)

• Rubella (state) (key: Röteln (Meldepflicht gemäß Landesmeldeverordnung))

• Rubella, congenital (key: Röteln, konnatal)

• SARS (key: SARS)

• Salmonellosis (key: Salmonellose)

• Scabies (key: Krätzmilbenbefall)

• Scarlet fever (key: Scharlach)

• Sepsis (other) (key: Weitere bedrohliche Krankheit)

• Shigellosis (key: Shigellose)

• Smallpox (key: Pocken)

• Subacute Sclerosing Panencephalitis (key: Subakute Sklerosierende Panenzephalitis)

• Syphilis (key: Syphilis)

• Tetanus (key: Tetanus)

• Tick bourne encephalitis (key: FSME (Frühsommer-Meningoenzephalitis))

• Toxoplasmosis (key: Toxoplasmose)

• Toxoplasmosis, congenital (key: Toxoplasmose, konnatal)

• Trichinellosis (key: Trichinellose)

• Tuberculosis (key: Tuberkulose)

• Tulareamia (key: Tularämie)

• Typhoid (key: Fleckfieber)

• Typhoid, abdominal (key: Typhus abdominalis)

• Typhus/Paratyphus (key: Typhus/Paratyphus)

• Varicella, congenital (key: Fetales (kongenitales) Varizellensyndrom)

• Vibria (key: Vibrionen)

• Viral haemmorhagic fever (key: Virale hämorrhagische Fieber)

• West Nile Virus (key: West-Nil-Virus)

• Whooping cough (IfSG) (key: Keuchhusten (Meldepflicht gemäß IfSG))

• Whooping cough (state) (key: Keuchhusten (Meldepflicht gemäß Landesmeldeverordnung))

• Yellow fever (key: Gelbfieber)

• Yersinia (key: Yersiniose)

• Zika (key: Zikavirus-Erkrankung)

Usage

diseases

Format

An object of class list of length 121.

References

https://survstat.rki.de/Content/Query/Create.aspx

---

The FedStateKey71Map dataset.

Description

This matches the FedStateKey71 dimension in SurvStat. This is the 16 federal states in Germany.

Usage

data(FedStateKey71Map)

Format

A sf dataframe containing the following columns:

• Id - the full SurvStat identifier for this region (includes hierarchical information)

• ComponentId - the id of the most granular geographical unit (which can be used to link out to other data sets)

• HierarchyId - the id of the geographical unit type

• Name - the name of the region

16 rows

---

Infer and fit a population model from SurvStat output

Description

SurvStat can be queried for count or incidence. From the combination of these metrics queried across the whole range of disease notifications for any given year we can infer a stratified population size, that SurvStat is using to calculate it's incidence. This is simply modelled with a local polynomial over time to allow us to fill in weekly population denominators.

Usage

fit_population(count_df, .progress = TRUE)

infer_population(
  age_group = NULL,
  geography = NULL,
  years = NULL,
  .progress = TRUE
)

Arguments

count_df	a dataframe from the output of get_timeseries() or get_snapshot()
.progress	by default a progress bar is shown, which may be important if many downloads are needed to fulfil the request. It can be disabled by setting this to FALSE here.
age_group	(optional) the age group of interest as a SurvStat key, see rsurvstat::age_groups for a list of valid options.
geography	(optional) one of "state", "nuts", or "county" to define the resolution of the query. Does not accept a sf map or subset of (unlike get_timeseries()).
years	(optional) a vector of years to limit the response to. This may be useful to limit the size of returned pages in the event the SurvStat service hits a data transfer limit.

Value

the count_df dataframe with an additional population column

a dataframe with geography, age grouping, year and population columns

Functions

• infer_population(): Query SurvStat for data to impute a population denominator

Examples

# snapshot:
get_snapshot(
  disease = diseases$`COVID-19`,
  geography = "state",
  season=2024
) %>%
fit_population() %>%
dplyr::glimpse()

# timeseries
# A weekly population estimate is inferred from the yearly data:
get_timeseries(
  diseases$`COVID-19`,
  measure = "Count",
  age_group = age_groups$children_coarse
) %>%
fit_population() %>%
dplyr::glimpse()



infer_population(years=2020:2025) %>% dplyr::glimpse()

---

Retrieve data from the SurvStat web service relating to a single time period.

Description

This function gets a snapshot of disease count or incidence data from the Robert Koch Institute SurvStat web service, based on either whole epidemiological season or an individual week within a season. Seasons are whole years starting either at the beginning of the calendar year, at week 27 or at week 40.

Usage

get_snapshot(
  disease = NULL,
  measure = c("Count", "Incidence"),
  ...,
  season,
  season_week = NULL,
  season_start = 1,
  age_group = NULL,
  age_range = c(0, Inf),
  disease_subtype = FALSE,
  geography = NULL,
  .progress = TRUE
)

Arguments

disease	the disease of interest as a SurvStat key, see rsurvstat::diseases for a current list of these. This is technically optional, and if omitted the counts of all diseases will be returned. Keys are the same as the options in the SurvStat user interface found here. IfSG and state variants of diseases are counts that are reported directly to the Robert Koch Institute or indirectly via state departments.
measure	one of "Count" (default) or "Incidence" per 100,000 per week or year depending on the context.
...	not used, must be empty.
season	the start year of the season in which the snapshot is taken
season_week	the start week within the season of the snapshot. If missing then the whole season is used
season_start	the week of the calendar year in which the season starts this can be one of 1, 27 or 40.
age_group	(optional) the age group of interest as a SurvStat key, see rsurvstat::age_groups for a list of valid options.
age_range	(optional) a length 2 vector with the minimum and maximum ages to consider
disease_subtype	if TRUE the returned count will be broken down by disease or pathogen subtype (assuming disease was provided).
geography	(optional) a geographical breakdown. This can be given as a character where it must be one of state, nuts, or county specifying the 16 region FedStateKey71Map, 38 region NutsKey71Map, or 411 region CountyKey71Map data respectively. Alternatively it can be given as a as a sf dataframe, subsetting one of these maps, in which case only that subset of regions will be returned.
.progress	by default a progress bar is shown, which may be important if many downloads are needed to fulfil the request. It can be disabled by setting this to FALSE here.

Details

The snapshot can be stratified by any combination of age, geography, disease, disease subtype. Queries to SurvStat are cached and paged, but obviously multidimensional extracts have the potential to need a lot of downloading.

Value

a data frame with at least year (the start of the epidemiological season) and start_week (the calendar week in which the epidemiological season starts), and one of count or incidence columns. Most likely it will also have disease_name and disease_code columns, and some of age_name, age_code, age_low, age_high, geo_code, geo_name, disease_subtype_code, disease_subtype_name depending on options.

Examples

get_snapshot(
  diseases$`COVID-19`,
  measure = "Count",
  season = 2024,
  age_group = age_groups$children_coarse
)

get_snapshot(
  diseases$`COVID-19`,
  measure = "Count",
  age_group = age_groups$children_coarse,
  season = 2024,
  geography = rsurvstat::FedStateKey71Map[1:10,]
)

---

Retrieve time series data from the SurvStat web service.

Description

This function gets a weekly timeseries of disease count or incidence data from the Robert Koch Institute SurvStat web service. The timeseries can be stratified by any combination of age, geography, disease, disease subtype. Queries to SurvStat are cached and paged, but obviously multidimensional extracts have the potential to need a lot of downloading.

Usage

get_timeseries(
  disease = NULL,
  measure = c("Count", "Incidence"),
  ...,
  age_group = NULL,
  age_range = c(0, Inf),
  disease_subtype = FALSE,
  years = NULL,
  geography = NULL,
  trim_zeros = c("leading", "both", "none"),
  .progress = TRUE
)

Arguments

disease	the disease of interest as a SurvStat key, see rsurvstat::diseases for a current list of these. This is technically optional, and if omitted the counts of all diseases will be returned. Keys are the same as the options in the SurvStat user interface found here. IfSG and state variants of diseases are counts that are reported directly to the Robert Koch Institute or indirectly via state departments.
measure	one of "Count" (default) or "Incidence" per 100,000 per week or year depending on the context.
...	not used, must be empty.
age_group	(optional) the age group of interest as a SurvStat key, see rsurvstat::age_groups for a list of valid options.
age_range	(optional) a length 2 vector with the minimum and maximum ages to consider
disease_subtype	if TRUE the returned count will be broken down by disease or pathogen subtype (assuming disease was provided).
years	(optional) a vector of years to limit the response to. This may be useful to limit the size of returned pages in the event the SurvStat service hits a data transfer limit.
geography	(optional) a geographical breakdown. This can be given as a character where it must be one of state, nuts, or county specifying the 16 region FedStateKey71Map, 38 region NutsKey71Map, or 411 region CountyKey71Map data respectively. Alternatively it can be given as a as a sf dataframe, subsetting one of these maps, in which case only that subset of regions will be returned.
trim_zeros	get rid of zero counts. Either "both" (from start and end), "leading" (from start only - the default) or "none".
.progress	by default a progress bar is shown, which may be important if many downloads are needed to fulfil the request. It can be disabled by setting this to FALSE here.

Value

a data frame with at least date (weekly), and one of count or incidence columns. Most likely it will also have disease_name and disease_code columns, and some of age_name, age_code, age_low, age_high, geo_code, geo_name, disease_subtype_code, disease_subtype_name depending on options. The dataframe will be grouped to make sure each group contains a single timeseries.

Examples

# age stratified
get_timeseries(
  diseases$`COVID-19`,
  measure = "Count",
  age_group = age_groups$children_coarse
) %>% dplyr::glimpse()

# geographic
get_timeseries(
  diseases$`COVID-19`,
  measure = "Count",
  geography = "state"
) %>% dplyr::glimpse()

# disease stratified, subset of years:
get_timeseries(
  measure = "Count",
  years = 2024
) %>% dplyr::glimpse()

---

The NutsKey71Map dataset

Description

This matches the NutsKey71 dimension in SurvStat. This is the 38 NUTS2 level administrative regions in Germany.

Usage

data(NutsKey71Map)

Format

A sf dataframe containing the following columns:

• Id - the full SurvStat identifier for this region (includes hierarchical information)

• ComponentId - the id of the most granular geographical unit (which can be used to link out to other data sets)

• HierarchyId - the id of the geographical unit type

• Name - the name of the region

38 rows

---

Set options for the rsurvstat cache

Description

By default successful requests to SurvStat are cached for 7 days to prevent repeated querying of the service. This is stored in the usual R package cache location by default (e.g. "~/.cache/rsurvstat" on mac / linux). Caching can be switched off altogether.

Usage

set_cache_settings(..., active = NULL, dir = NULL, stale = NULL)

Arguments

...	you can also submit the settings as a named list.
active	boolean (optional), set to FALSE to disable caching
dir	file path (optional), the location of the cache
stale	numeric (optional), the number of days before a cached item is considered out of date

Value

the old cache settings as a list

Examples

old_settings = set_cache_settings(active = FALSE)
set_cache_settings(old_settings)

---