Package 'epiCo'

Returns the specific rates associated with being infected given age and sex

Description

Function that returns the specific rates of being infected given age and sex

Usage

age_risk(age, population_pyramid, sex = NULL, plot = FALSE)

Arguments

age	A vector with the ages of cases in years from 0 to 100 years
population_pyramid	A dataframe with the count of individuals with the columns age, population and sex
sex	A vector with the sex of cases 'F' and 'M'. The default value is NULL
plot	A boolean for displaying a plot. The default value is FALSE

Value

A dataframe with the proportion or total count of individuals

Examples

pop_pyramid <- population_pyramid("15001", 2015,
  sex = TRUE, total = TRUE,
  plot = FALSE
)
ages <- round(runif(150, 0, 100))
sex <- c(rep("M", 70), rep("F", 80))
age_risk(
  age = ages, sex = sex, population_pyramid = pop_pyramid,
  plot = TRUE
)

---

Provides the sociological description of ethnicities in Colombia

Description

Function that returns the description of the consulted ethnicities

Usage

describe_ethnicity(ethnic_codes)

Arguments

ethnic_codes

A numeric vector with the codes of ethnicities to consult

Value

A printed message with ethnicities descriptions

Examples

describe_ethnicity(round(runif(n = 150, min = 1, max = 4)))

---

Get ISCO-88 occupation labels from codes

Description

Function that translates a vector of ISCO-88 occupation codes into a vector of labels

Usage

describe_occupation(isco_codes, sex = NULL, plot = NULL)

Arguments

isco_codes	A numeric vector of ISCO-88 occupation codes (major, submajor, minor, or unit)
sex	A vector with the respective sex for isco_codes vector. The default value is NULL
plot	A type of plot between treemap and circular packing. The default value is NULL

Value

A string vector of ISCO-88 labels

Examples

demog_data <- data.frame(
  occupation_label =
    c(6111, 3221, 5113, 5133, 6111, 23, 25),
  sex = c("F", "M", "F", "F", "M", "M", "F")
)
describe_occupation(
  isco_codes = demog_data$occupation_label,
  sex = demog_data$sex, plot = "treemap"
)

---

divipola_table

Description

Political and administrative distribution of Colombia's municipalities

Usage

data(divipola_table)

Format

An object of class data.frame with 1121 rows and 8 columns.

Details

DIVIPOLA table

---

Create and return the endemic channel of a disease from an incidence object

Description

Function that builds the endemic channel of a disease time series based on the selected method and windows of observation

Usage

endemic_channel(
  incidence_historic,
  observations = NULL,
  method = c("geometric", "median", "mean", "unusual_behavior"),
  geometric_method = "shifted",
  outlier_years = NULL,
  outliers_handling = c("ignored", "included", "replaced_by_median", "replaced_by_mean",
    "replaced_by_geometric_mean"),
  ci = 0.95,
  plot = FALSE
)

Arguments

incidence_historic	An incidence object with the historic weekly observations
observations	A numeric vector with the current observations
method	A string with the mean calculation method of preference (median, mean, or geometric) or to use the unusual behavior method (Poisson Distribution Test for Hypoendemic settings)
geometric_method	A string with the selected method for geometric mean calculation; see: geometric_mean
outlier_years	A numeric vector with the outlier years
outliers_handling	A string with the handling decision regarding outlier years, see: outliers_handling function
ci	= 0.95 A numeric value to specify the confidence interval to use with the geometric method
plot	A boolean for displaying a plot

Value

A dataframe with the observation, historical mean, and confidence intervals (or risk areas)

Examples

data_event <- epiCo::epi_data
data_ibague <- data_event[data_event$cod_mun_o == 73001, ]
incidence_historic <- incidence::incidence(data_ibague$fec_not,
  interval = "1 epiweek"
)
endemic_channel(incidence_historic,
  method = "geometric", plot = TRUE
)

---

Get the epidemiological calendar of a consulted year.

Description

Function that returns the starting date of the epidemiological weeks in a year of interest.

Usage

epi_calendar(year, jan_days = 4)

Arguments

year	A numeric value for the year of interest.
jan_days	Number of January days that the first epidemiological week must contains.

Value

A character array with the starting dates of the epidemiological weeks of the given year.

Examples

epi_calendar(2016)

---

epi_data

Description

Epidemiological data for the Tolima department for the years 2012 to 2022

Usage

data(epi_data)

Format

An object of class tbl_df (inherits from tbl, data.frame) with 66747 rows and 16 columns.

Details

Epidemiological data

---

Returns the geometric mean of a vector of real numbers.

Description

Function that returns the geometric mean of a vector of real numbers according to the selected method.

Usage

geometric_mean(
  x,
  method = c("positive", "shifted", "optimized", "weighted"),
  shift = 1,
  epsilon = 0.001
)

Arguments

x	A numeric vector of real values
method	Description of methods: positive = only positive values within x are used in the calculation. shifted = positive and zero values within x are used by adding a shift value before the calculation and subtracting it to the final result. optimized = optimized shifted method. See: De La Cruz, R., & Kreft, J. U. (2018). Geometric mean extension for data sets with zeros. arXiv preprint arXiv:1806.06403. weighted = a probability weighted calculation of gm for negative, positive, and zero values. See: Habib, E. A. (2012). Geometric mean for negative and zero values. International Journal of Research and Reviews in Applied Sciences, 11(3), 419-432.
shift	= 1 (default) a positive value to use in the shifted method
epsilon	= 1e-5 (default) the minimum positive value to consider in the optimized method.

Value

The geometric mean of the x vector, and the epsilon value if optimized method is used.

Examples

x <- c(4, 5, 3, 7, 8)
geometric_mean(x, method = "optimized")

---

Returns the geometric standard deviation of a vector of real numbers.

Description

Function that returns the geometric standard deviation of a vector of real numbers according to the selected method.

Usage

geometric_sd(
  x,
  method = c("positive", "shifted", "optimized", "weighted"),
  shift = 1,
  delta = 0.001
)

Arguments

x	A numeric vector of real values
method	Description of methods: positive = only positive values within x are used in the calculation. shifted = positive and zero values within x are used by adding a shift value before the calculation and subtracting it to the final result. optimized = optimized shifted method. See: De La Cruz, R., & Kreft, J. U. (2018). Geometric mean extension for data sets with zeros. arXiv preprint arXiv:1806.06403. weighted = a probability weighted calculation of gm for negative, positive, and zero values. See: Habib, E. A. (2012). Geometric mean for negative and zero values. International Journal of Research and Reviews in Applied Sciences, 11(3), 419-432.
shift	a positive value to use in the shifted method
delta	an positive value (shift) used in the optimized method.

Value

The geometric mean of the x vector, and the epsilon value if optimized method is used.

Examples

x <- c(4, 5, 3, 7, 8)
geometric_sd(x, method = "optimized")

---

Extends an incidence class object with incidence rates estimations.

Description

Function that estimates incidence rates from a incidence class object and population projections.

Usage

incidence_rate(incidence_object, level, scale = 1e+05)

Arguments

incidence_object	An incidence object.
level	Administration level at which incidence counts are grouped (0 = national, 1 = state/department, 2 = city/municipality).
scale	Scale to consider when calculating the incidence_rate.

Value

A modified incidence object where counts are normalized with the population.

Examples

data_event <- epiCo::epi_data
incidence_historic <- incidence::incidence(data_event$fec_not,
  groups = data_event$cod_mun_o,
  interval = "1 year"
)
incidence_object <- subset(incidence_historic,
  from = "2015-01-04",
  to = "2018-12-27"
)
inc_rate <- incidence_rate(incidence_object, level = 2, scale = 100000)
inc_rate$rates

---

isco88_table

Description

ISCO88 description of occupations

Usage

data(isco88_table)

Format

An object of class data.frame with 390 rows and 8 columns.

Details

ISCO88 occupation table

---

Calculate spatial correlation of given municipalities in an incidence_rate object.

Description

Function to calculate spatial autocorrelation via Moran's Index from a given incidence_rate object grouped by municipality.

Usage

morans_index(incidence_object, scale = 1e+05, threshold = 2, plot = TRUE)

Arguments

incidence_object	An incidence object with one observation for the different locations (groups).
scale	Scale to consider when calculating the incidence_rate.
threshold	Maximum traveling time around each municipality.
plot	if TRUE, returns a plot of influential observations in the Moran's plot.

Value

List of Moran's I clustering analysis, giving the quadrant of each observation, influential values.

Examples

data_event <- epiCo::epi_data
incidence_historic <- incidence::incidence(data_event$fec_not,
  groups = data_event$cod_mun_o,
  interval = "4 year"
)
incidence_object <- subset(incidence_historic,
  from = "2015-01-04",
  to = "2018-12-27"
)
morans_index(incidence_object, scale = 100000, threshold = 2, plot = TRUE)

---

Neighborhoods from real travel distances in Colombia

Description

Function to build neighborhoods from real travel distances inside Colombia by land or river transportation.

Usage

neighborhoods(query_vector, threshold = 2)

Arguments

query_vector	Codes of the municipalities to consider for the neighborhoods.
threshold	Maximum traveling time around each municipality.

Value

neighborhood object according to the introduced threshold.

Examples

query_vector <- c("05001", "05002", "05004", "05021", "05030", "05615")
neighborhoods(query_vector, 2)

---

Returns the population pyramid of the consulted region

Description

Function that returns the population pyramid of the municipality or department of a specific year

Usage

population_pyramid(
  divipola_code,
  year,
  sex = TRUE,
  range = 5,
  total = TRUE,
  plot = FALSE
)

Arguments

divipola_code	A code from the divipola table representing a department or municipality. To obtain values at the national level, code '0' is used
year	A numeric input for the year of interest
sex	A boolean to consult data disaggregated by sex. The default value is TRUE
range	A numeric value from 1 to 100 for the age range to use. The default value is 5
total	A boolean for returning the total number rather than the proportion of the country's population. The default value is TRUE
plot	A boolean for displaying a plot. The default value is TRUE

Value

A dataframe with the proportion or total count of individuals

Examples

population_pyramid("15001", 2015, sex = TRUE, total = TRUE, plot = TRUE)

---