Análisis COVID‑19: casos y vacunación
Rocio Viveros
2025-06-23
1 Cargar datos limpios
df <- read_parquet("covid_owid_limpio.parquet")
skim(df)| Name | df |
| Number of rows | 429435 |
| Number of columns | 68 |
| _______________________ | |
| Column type frequency: | |
| character | 4 |
| Date | 1 |
| numeric | 63 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| iso_code | 0 | 1.00 | 3 | 8 | 0 | 255 | 0 |
| continent | 26525 | 0.94 | 4 | 13 | 0 | 6 | 0 |
| pais | 0 | 1.00 | 4 | 32 | 0 | 255 | 0 |
| tests_units | 322647 | 0.25 | 13 | 15 | 0 | 4 | 0 |
Variable type: Date
| skim_variable | n_missing | complete_rate | min | max | median | n_unique |
|---|---|---|---|---|---|---|
| date | 0 | 1 | 2020-01-01 | 2024-08-14 | 2022-04-20 | 1688 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| casos_totales | 17631 | 0.96 | 7365292.35 | 4.477582e+07 | 0.00 | 6280.75 | 63653.00 | 758272.00 | 7.758668e+08 | ▇▁▁▁▁ |
| casos_nuevos | 19276 | 0.96 | 8017.36 | 2.296649e+05 | 0.00 | 0.00 | 0.00 | 0.00 | 4.423623e+07 | ▇▁▁▁▁ |
| new_cases_smoothed | 20506 | 0.95 | 8041.03 | 8.661611e+04 | 0.00 | 0.00 | 12.00 | 313.29 | 6.319461e+06 | ▇▁▁▁▁ |
| muertes_totales | 17631 | 0.96 | 81259.57 | 4.411901e+05 | 0.00 | 43.00 | 799.00 | 9574.00 | 7.057132e+06 | ▇▁▁▁▁ |
| muertes_nuevas | 18827 | 0.96 | 71.85 | 1.368320e+03 | 0.00 | 0.00 | 0.00 | 0.00 | 1.037190e+05 | ▇▁▁▁▁ |
| new_deaths_smoothed | 20057 | 0.95 | 72.06 | 5.136400e+02 | 0.00 | 0.00 | 0.00 | 3.14 | 1.481700e+04 | ▇▁▁▁▁ |
| total_cases_per_million | 17631 | 0.96 | 112096.20 | 1.622404e+05 | 0.00 | 1916.10 | 29145.48 | 156770.19 | 7.635986e+05 | ▇▁▁▁▁ |
| new_cases_per_million | 19276 | 0.96 | 122.36 | 1.508780e+03 | 0.00 | 0.00 | 0.00 | 0.00 | 2.417582e+05 | ▇▁▁▁▁ |
| new_cases_smoothed_per_million | 20506 | 0.95 | 122.71 | 5.597000e+02 | 0.00 | 0.00 | 2.79 | 56.25 | 3.453689e+04 | ▇▁▁▁▁ |
| total_deaths_per_million | 17631 | 0.96 | 835.51 | 1.134930e+03 | 0.00 | 24.57 | 295.09 | 1283.82 | 6.601110e+03 | ▇▂▁▁▁ |
| new_deaths_per_million | 18827 | 0.96 | 0.76 | 6.980000e+00 | 0.00 | 0.00 | 0.00 | 0.00 | 8.936600e+02 | ▇▁▁▁▁ |
| new_deaths_smoothed_per_million | 20057 | 0.95 | 0.76 | 2.550000e+00 | 0.00 | 0.00 | 0.00 | 0.36 | 1.276600e+02 | ▇▁▁▁▁ |
| reproduction_rate | 244618 | 0.43 | 0.91 | 4.000000e-01 | -0.07 | 0.72 | 0.95 | 1.14 | 5.870000e+00 | ▇▃▁▁▁ |
| icu_patients | 390319 | 0.09 | 660.97 | 2.139620e+03 | 0.00 | 21.00 | 90.00 | 413.00 | 2.889100e+04 | ▇▁▁▁▁ |
| icu_patients_per_million | 390319 | 0.09 | 15.66 | 2.279000e+01 | 0.00 | 2.33 | 6.43 | 18.78 | 1.806800e+02 | ▇▁▁▁▁ |
| hosp_patients | 388779 | 0.09 | 3911.74 | 9.845750e+03 | 0.00 | 186.00 | 776.00 | 3051.00 | 1.544970e+05 | ▇▁▁▁▁ |
| hosp_patients_per_million | 388779 | 0.09 | 125.99 | 1.511600e+02 | 0.00 | 31.00 | 74.24 | 159.76 | 1.526850e+03 | ▇▁▁▁▁ |
| weekly_icu_admissions | 418442 | 0.03 | 317.89 | 5.144100e+02 | 0.00 | 17.00 | 92.00 | 353.00 | 4.838000e+03 | ▇▁▁▁▁ |
| weekly_icu_admissions_per_million | 418442 | 0.03 | 9.67 | 1.357000e+01 | 0.00 | 1.55 | 4.64 | 12.65 | 2.249800e+02 | ▇▁▁▁▁ |
| weekly_hosp_admissions | 404938 | 0.06 | 4291.72 | 1.091962e+04 | 0.00 | 223.00 | 864.00 | 3893.00 | 1.539770e+05 | ▇▁▁▁▁ |
| weekly_hosp_admissions_per_million | 404938 | 0.06 | 82.62 | 8.840000e+01 | 0.00 | 23.73 | 56.28 | 110.00 | 7.170800e+02 | ▇▁▁▁▁ |
| total_tests | 350048 | 0.18 | 21104573.94 | 8.409869e+07 | 0.00 | 364654.00 | 2067330.00 | 10248451.50 | 9.214000e+09 | ▇▁▁▁▁ |
| new_tests | 354032 | 0.18 | 67285.41 | 2.477340e+05 | 1.00 | 2244.00 | 8783.00 | 37229.00 | 3.585563e+07 | ▇▁▁▁▁ |
| total_tests_per_thousand | 350048 | 0.18 | 924.25 | 2.195430e+03 | 0.00 | 43.58 | 234.14 | 894.38 | 3.292583e+04 | ▇▁▁▁▁ |
| new_tests_per_thousand | 354032 | 0.18 | 3.27 | 9.030000e+00 | 0.00 | 0.29 | 0.97 | 2.91 | 5.310600e+02 | ▇▁▁▁▁ |
| new_tests_smoothed | 325470 | 0.24 | 142178.36 | 1.138215e+06 | 0.00 | 1486.00 | 6570.00 | 32205.00 | 1.476998e+07 | ▇▁▁▁▁ |
| new_tests_smoothed_per_thousand | 325470 | 0.24 | 2.83 | 7.310000e+00 | 0.00 | 0.20 | 0.85 | 2.58 | 1.476000e+02 | ▇▁▁▁▁ |
| positive_rate | 333508 | 0.22 | 0.10 | 1.200000e-01 | 0.00 | 0.02 | 0.06 | 0.14 | 1.000000e+00 | ▇▁▁▁▁ |
| tests_per_case | 335087 | 0.22 | 2403.63 | 3.344366e+04 | 1.00 | 7.10 | 17.50 | 54.60 | 1.023632e+06 | ▇▁▁▁▁ |
| vacunas_totales | 344018 | 0.20 | 561697983.43 | 1.842160e+09 | 0.00 | 1970788.00 | 14394348.00 | 116197175.00 | 1.357877e+10 | ▇▁▁▁▁ |
| vacunados_una_dosis | 348303 | 0.19 | 248706410.74 | 8.006461e+08 | 0.00 | 1050009.25 | 6901087.50 | 50932952.00 | 5.631264e+09 | ▇▁▁▁▁ |
| vacunados_completos | 351374 | 0.18 | 228663910.07 | 7.403763e+08 | 1.00 | 964400.00 | 6191345.00 | 47731850.00 | 5.177943e+09 | ▇▁▁▁▁ |
| refuerzos | 375835 | 0.12 | 150581058.90 | 4.360697e+08 | 1.00 | 602282.00 | 5765440.00 | 40190716.25 | 2.817381e+09 | ▇▁▁▁▁ |
| new_vaccinations | 358464 | 0.17 | 739864.03 | 3.183064e+06 | 0.00 | 2010.00 | 20531.00 | 173611.50 | 4.967320e+07 | ▇▁▁▁▁ |
| new_vaccinations_smoothed | 234406 | 0.45 | 283875.82 | 1.922352e+06 | 0.00 | 279.00 | 3871.00 | 31803.00 | 4.369181e+07 | ▇▁▁▁▁ |
| total_vaccinations_per_hundred | 344018 | 0.20 | 124.28 | 8.510000e+01 | 0.00 | 44.77 | 130.55 | 194.99 | 4.102300e+02 | ▇▆▆▁▁ |
| people_vaccinated_per_hundred | 348303 | 0.19 | 53.50 | 2.938000e+01 | 0.00 | 27.88 | 64.30 | 77.78 | 1.290700e+02 | ▆▃▇▆▁ |
| people_fully_vaccinated_per_hundred | 351374 | 0.18 | 48.68 | 2.904000e+01 | 0.00 | 21.22 | 57.92 | 73.61 | 1.268900e+02 | ▆▃▇▅▁ |
| total_boosters_per_hundred | 375835 | 0.12 | 36.30 | 3.022000e+01 | 0.00 | 5.92 | 35.91 | 57.62 | 1.504700e+02 | ▇▆▃▁▁ |
| new_vaccinations_smoothed_per_million | 234406 | 0.45 | 1851.48 | 3.117830e+03 | 0.00 | 106.00 | 605.00 | 2402.00 | 1.171130e+05 | ▇▁▁▁▁ |
| new_people_vaccinated_smoothed | 237258 | 0.45 | 106070.70 | 7.866884e+05 | 0.00 | 43.00 | 771.00 | 9307.00 | 2.107127e+07 | ▇▁▁▁▁ |
| new_people_vaccinated_smoothed_per_hundred | 237258 | 0.45 | 0.07 | 1.800000e-01 | 0.00 | 0.00 | 0.01 | 0.07 | 1.171000e+01 | ▇▁▁▁▁ |
| stringency_index | 233245 | 0.46 | 42.88 | 2.487000e+01 | 0.00 | 22.22 | 42.85 | 62.04 | 1.000000e+02 | ▇▆▇▆▂ |
| population_density | 68943 | 0.84 | 394.07 | 1.785450e+03 | 0.14 | 37.73 | 88.12 | 222.87 | 2.054677e+04 | ▇▁▁▁▁ |
| median_age | 94772 | 0.78 | 30.46 | 9.090000e+00 | 15.10 | 22.20 | 29.70 | 38.70 | 4.820000e+01 | ▇▆▇▆▆ |
| aged_65_older | 106165 | 0.75 | 8.68 | 6.090000e+00 | 1.14 | 3.53 | 6.29 | 13.93 | 2.705000e+01 | ▇▃▂▂▁ |
| aged_70_older | 98120 | 0.77 | 5.49 | 4.140000e+00 | 0.53 | 2.06 | 3.87 | 8.64 | 1.849000e+01 | ▇▃▂▂▁ |
| gdp_per_capita | 101143 | 0.76 | 18904.18 | 1.982958e+04 | 661.24 | 4227.63 | 12294.88 | 27216.44 | 1.169356e+05 | ▇▂▁▁▁ |
| extreme_poverty | 217439 | 0.49 | 13.92 | 2.007000e+01 | 0.10 | 0.60 | 2.50 | 21.40 | 7.760000e+01 | ▇▂▁▁▁ |
| cardiovasc_death_rate | 100570 | 0.77 | 264.64 | 1.207600e+02 | 79.37 | 175.70 | 245.46 | 333.44 | 7.244200e+02 | ▇▇▃▁▁ |
| diabetes_prevalence | 83524 | 0.81 | 8.56 | 4.930000e+00 | 0.99 | 5.35 | 7.20 | 10.79 | 3.053000e+01 | ▇▇▂▁▁ |
| female_smokers | 182270 | 0.58 | 10.77 | 1.076000e+01 | 0.10 | 1.90 | 6.30 | 19.30 | 4.400000e+01 | ▇▂▂▁▁ |
| male_smokers | 185618 | 0.57 | 33.10 | 1.385000e+01 | 7.70 | 22.60 | 33.10 | 41.50 | 7.810000e+01 | ▆▇▆▂▁ |
| handwashing_facilities | 267694 | 0.38 | 50.65 | 3.191000e+01 | 1.19 | 20.86 | 49.54 | 82.50 | 1.000000e+02 | ▇▅▅▅▇ |
| hospital_beds_per_thousand | 138746 | 0.68 | 3.11 | 2.550000e+00 | 0.10 | 1.30 | 2.50 | 4.21 | 1.380000e+01 | ▇▃▂▁▁ |
| life_expectancy | 39136 | 0.91 | 73.70 | 7.390000e+00 | 53.28 | 69.50 | 75.05 | 79.46 | 8.675000e+01 | ▁▃▅▇▅ |
| human_development_index | 110308 | 0.74 | 0.72 | 1.500000e-01 | 0.39 | 0.60 | 0.74 | 0.83 | 9.600000e-01 | ▂▅▅▇▆ |
| population | 0 | 1.00 | 152033640.40 | 6.975408e+08 | 47.00 | 523798.00 | 6336393.00 | 32969520.00 | 7.975105e+09 | ▇▁▁▁▁ |
| excess_mortality_cumulative_absolute | 416024 | 0.03 | 56047.65 | 1.568691e+05 | -37726.10 | 176.50 | 6815.20 | 39128.04 | 1.349776e+06 | ▇▁▁▁▁ |
| excess_mortality_cumulative | 416024 | 0.03 | 9.77 | 1.204000e+01 | -44.23 | 2.06 | 8.13 | 15.16 | 7.808000e+01 | ▁▃▇▁▁ |
| excess_mortality | 416024 | 0.03 | 10.93 | 2.456000e+01 | -95.92 | -1.50 | 5.66 | 15.57 | 3.782200e+02 | ▃▇▁▁▁ |
| excess_mortality_cumulative_per_million | 416024 | 0.03 | 1772.67 | 1.991890e+03 | -2936.45 | 116.88 | 1270.80 | 2883.02 | 1.029352e+04 | ▁▇▃▁▁ |
| casos_por_vacuna | 355903 | 0.17 | 42.78 | 8.187780e+03 | 0.00 | 0.00 | 0.00 | 0.00 | 2.100420e+06 | ▇▁▁▁▁ |
2 Dosis de refuerzo aplicadas globalmente
df %>%
group_by(date) %>%
summarise(total_refuerzos = sum(refuerzos, na.rm = TRUE)) %>%
ggplot(aes(date, total_refuerzos)) +
geom_line(color = "darkgreen") +
labs(title = "Dosis de refuerzo aplicadas globalmente",
x = "Fecha", y = "Cantidad de dosis")
3 Casos nuevos vs vacunación completa (países seleccionados)
paises <- c("Paraguay", "Argentina", "Brasil", "Chile")
df %>%
filter(pais %in% paises) %>%
ggplot(aes(date)) +
geom_line(aes(y = casos_nuevos, color = "Casos nuevos")) +
geom_line(aes(y = vacunados_completos, color = "Vacunados completos")) +
facet_wrap(~pais, scales = "free_y") +
labs(title = "Casos vs vacunación completa",
x = "Fecha", color = "Indicador")
4 Top 10 países por vacunación completa
df %>%
filter(date == max(date)) %>%
arrange(desc(vacunados_completos)) %>%
slice_head(n = 10) %>%
select(pais, vacunados_completos, casos_totales, muertes_totales) %>%
knitr::kable()| pais | vacunados_completos | casos_totales | muertes_totales |
|---|---|---|---|
| World | 5177942957 | NA | NA |
| Asia | 3462095463 | NA | NA |
| Upper-middle-income countries | 1990653301 | NA | NA |
| High-income countries | 929255961 | NA | NA |
| Europe | 493751304 | NA | NA |
| European Union (27) | 327967426 | NA | NA |
| Malaysia | 27551144 | NA | NA |
| Lithuania | 1881106 | NA | NA |
5 Metodología
El análisis se basa en datos proporcionados por Our World in Data, una fuente de datos abiertos ampliamente reconocida. Se aplicaron los siguientes pasos metodológicos:
- Obtención del dataset: Descarga directa desde GitHub en formato CSV.
- Preparación de datos:
- Limpieza de columnas (nombres, duplicados y valores faltantes).
- Conversión de fechas y selección de variables clave.
- Creación de variables derivadas, como casos por vacuna.
- Guardado en formato Parquet para eficiencia de almacenamiento.
- Análisis exploratorio:
- Evaluación temporal de dosis de refuerzo aplicadas a nivel global.
- Comparación entre países seleccionados (Paraguay, Argentina, Brasil y Chile) en términos de nuevos casos y vacunación completa.
- Ranking de países con mayor cantidad de personas con vacunación completa.
Se utilizaron librerías como tidyverse,
lubridate, arrow y ggplot2 para
todo el proceso.
6 Conclusiones
- La cantidad de dosis de refuerzo administradas globalmente ha seguido una tendencia creciente con variaciones por periodos, reflejando políticas de salud diferenciadas.
- En países como Chile y Brasil se observa una mayor proporción de población con vacunación completa en comparación con Paraguay.
- La relación entre nuevos casos y vacunación muestra que, a pesar del avance en las campañas de inmunización, la circulación del virus persiste, aunque en niveles más controlados en algunos contextos.
- La herramienta
Rpermite un análisis reproducible, escalable y transparente, lo que facilita la toma de decisiones basadas en evidencia.
Este trabajo puede extenderse con análisis por continente, tasas por población y relación con otras variables sociales o económicas.