An attempt to optimize human resources allocation based on spatial diversity of the first wave of COVID–19 in Poland
DOI:
https://doi.org/10.15503/emet2020.100.122Abstract
Aim. Our task was to examine the relationship between the SARS–CoV–2 arrival and the number of confi rmed COVID–19 cases in the fi rst wave (period from March 4 to May 22, 2020 (unoffi cial data)), and socio–economic variables at the powiat (county) level.
Methods. We were using simple statistical techniques such as data visualisation, correlation analysis, spatial clustering and multiple linear regression.
Results. We showed that immigration and the logarithm of general mobility was the best predictor of SARS–CoV–2 arrival times, while emigration, industrialisation and air quality explain most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population.
Conclusions. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution of human resources between poviats. Although this is
a retrospective analysis of the initial phase of the epidemic, similar patterns could repeat in case of new variants of SARS–CoV–2 or new respiratory disease for immunologically naive populations.
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References
Aldridge, R. W., Lewer, D., Katikireddi, S. V., Mathur, R., Pathak, N., Burns, R., . . . et al. (2020). Black, Asian and minority ethnic groups in England are at increased risk of death from Covid-19: indirect standardisation of NHS mortality data. Wellcome Open Research, 5(88), 88. https://doi.org/10.12688/wellcomeopenres.15922.2
AmbasadaKultury. (2020). Koronawirus mapa polski według powiatów [Coronavirus map of Poland for poviat]. Retrieved August 21, 2021, from https://t.co/iAqzy8brWG.
Bartosiak, J. (2019). Przeszłość jest prologiem [Past is prolog]. Zona Zero.
Bartscher, A. K., Seitz, S., Slotwinski, M., Siegloch, S., & Wehrhöfer, N. (2020). Social capital and the spread of Covid-19: Insights from European countries. Retrieved August 21, 2021, from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3623681. https://doi.org/10.1016/j.jhealeco.2021.102531
Belik, V., Geisel, T., & Brockmann, D. (2011). Natural human mobility patterns and spatial spread of infectious diseases. Physical Review X, 1(1), 011001. https://doi.org/10.1103/PhysRevX.1.011001
Chudy, F. (2020). Covid-19 prognoza [COVID-19 predictions]. Retrieved August 21, 2021, from https://docs.google.com/spreadsheets/d/1ZIdpVF5AfbkFvGxey92RQLjRVWF8_oWN5-hSbFDL8g0.
CNBC. (2020). How many contact tracers the u.k. has hired? Retrieved August 21, 2021, from https://www.cnbc.com/2020/05/18/uk-contact-tracer-jobs-confusion.html.
Conticini, E., Frediani, B., & Caro, D. (2020). Can atmospheric pollution be considered a cofactor in extremely high level of SARS-CoV–2 lethality in northern Italy? Environmental pollution, 261, 114465. https://doi.org/10.1016/j.envpol.2020.114465
Delhey, J., Verbalyte, M., Aplowski, A., & Deutschmann, E. (2019). Free to move: The evolution of the European migration network, 1960-2017. In: M. Heidenreich (Ed.). Horizontal Europeanisation, 63-84. Routledge.
Domański, H. (2020). Pandemia może być zjawiskiem wzmacniającym hierarchie społeczne [Pandemic may be a phenomenon that strengthens the social hierarchy]. Retrieved August 21, 2021, from http://naukawpolsce.pap.pl/aktualnosci/news%2C82066%2Cprofdomanski-pandemia-moze-byc-zjawiskiem-wzmacniajacym-hierarchie.
Drefahl, S., Wallace, M., Mussino, E., Kolk, M., Brandén, M., Malmberg, B., . . . Malmberg, B. (2020). Socio–demographic risk factors of Covid–19 deaths in Sweden: A nationwide register study. Stockholm Research Reports in Demography, 23. Retrieved August 21, 2021,
from https://su.fi gshare.com/articles/preprint/Socio-demographic_risk_factors_of_COVID-19_deaths_in_Sweden_A_nationwide_register_study/12420347. https://doi.org/10.1038/s41467-020-18926-3
Duplaga, M. (2020). Determinants and consequences of limited health literacy in Polish society. International Journal of Environmental Research and Public Health, 17(2), 642. https://doi.org/10.3390/ijerph17020642
Duszyński, J, et al. (2020). Zrozumieć covid–19 [Understand COVID–19]. Retrieved
August 21, 2021, from https://informacje.pan.pl/images/2020/opracowaniecovid19-14-09-2020/ZrozumiecCovid19_opracowanie_PAN_interactive.pdf.
ECDC. (2020). Enhanced surveillance data. Retrieved August 21, 2021, from https://qap.ecdc.europa.eu/public/extensions/COVID-19/COVID-19.html.
exmetrix. (2020). Najnowsza prognoza rozwoju pandemii covid–19 (The newest prediction of COVID–19 pandemic]. Retrieved August 21, 2021, from http://www.exmetrix.com/pl/posty/koronawirus-w-polsce-aktualna-prognoza-exmetrix/ .
Felbermayr, G., Hinz, J., & Chowdhry, S. (2020). Apres–ski: The spread of coronavirus from Ischgl through Germany. Retrieved August 21, 2021, from https://www.ifw-kiel.de/fi leadmin/Dateiverwaltung/IfW-Publications/Gabriel_Felbermayr/Apres-ski__The_Spread_of_Coronavirus_from_Ischgl_through_Germany/coronavirus_from_ischgl.pdf. https://doi.org/10.1515/ger-2020-0063
Gambin, A., & Rosińska, M. (2020). Covid–19. Retrieved August 21, 2021, from https://covid19.mimuw.edu.pl.
Gelfand, M., Jackson, J. C., Pan, X., Nau, D., Dagher, M., & Chiu, C.–Y. (2020). Cultural and institutional factors predicting the infection rate and mortality likelihood of the Covid–19 pandemic. PsyArXiv Preprints: https://psyarxiv. com/m7f8a.
GIOS. (2020). Narażenie na pył PM10 [Exposure of PM10]. Retrieved August 21, 2021, from http://powietrze.gios.gov.pl/pjp/airPollution .
GIS. (2020). Struktura zakażeń SARS–CoV–2 /8 kwietnia 2020 r./ [Composition of SARS–CoV–2 infections by 8.04.2020]. Retrieved August 21, 2021, from https://gis.gov.pl/bez–kategorii/struktura-zakazen-sars-cov-2-8-kwietnia/.
Gonczarek, A., & Wójcik, M. (2020). Jak przewidzieć rozwój epidemii sars cov–2 w polsce przy pomocy modeli matematycznych i uczenia maszynowego [How to predict the future of SARS–CoV–2 pandemic in Poland with mathematical models and machine learning?]. Retrieved August 21, 2021, from http://alphamoon.ai/blog/2020/03/25/jak-przewidziecrozwoj-pandemii-sars-cov-2-w-polsce/.
Górny, A., & Śleszyński, P. (2019). Exploring the spatial concentration of foreign employment in Poland under the simplifi ed procedure. Geographia Polonica, 92(3), 331–345. https://doi.org/10.7163/GPol.0152
GUS. (2020). Bank danych lokalnych [Local datasets]. Retrieved August 21, 2021, from https://bdl.stat.gov.pl/BDL/start.
GUS Poznan. (2020). Migracje pracownicze [Workforce migration]. https://poznan.stat.gov.pl.
Haug, N., Geyrhofer, L., Londei, A., Dervic, E., Desvars–Larrive, A., Loreto, V., ... & Klimek, P. (2020). Ranking the effectiveness of worldwide COVID–19 government interventions. Nature human behaviour, 4(12), 1303–1312. https://doi.org/10.1038/s41562-020-01009-0
Infodemia. (2020). Badanie kosztowej-efektywności interwencji mitygujących ryzyko zakażeń covid–19 przed falą jesienną [Study of the cost–effectiveness of interventions mitigating the risk of covid–19 infections before the second wave] . Retrieved August 21, 2021,
Jarynowski, A., Buda, A., & Nyczka, P. (2014). Obliczeniowe nauki społeczne w praktyce [Computational Social Science in Practice]. WN:Głogów.
Jarynowski, A., & Grabowski, A. (2019). Niewykorzystany potencjał systemów informatycznych w epidemiologii zakażeń szpitalnych w polsce (The unused potential of information systems in the epidemiology of hospital infections in Poland]. Collegium of Economic Analysis Annals, (56), 261–273.
Jarynowski, A., & Kliś, M. (2012). Socio–economic models of divorces in different societies. In: XVIII Krajowa Konferencja Zastosowań Matematyki w Biologii i Medycynie, Krynica Morska.
Jarynowski, A., Paradowski, M. B., & Buda, A. (2019). Modelling communities and populations: an introduction to computational social science. Studia metodologiczne, 39, 117–139. https://doi.org/10.14746/sm.2019.39.5
Jarynowski, A., Wójta–Kempa, M., & Belik, V. (2020a). Perception of “coronavirus” on the Polish Internet until arrival of SARS–CoV–2 in Poland. Piel Zdr Publ, 10(2). https://doi.org/10.17219/pzp/120054
Jarynowski, A., Wójta–Kempa, M., & Belik, V. (2020b). Trends in interest of covid–19 on Polish internet. Przegląd epidemiologiczny, 74(2), 106–123. https://doi.org/10.32394/pe.74.20
Jarynowski, A., Wójta–Kempa, M., Płatek, D., & Belik, V. (2020). Social values are significant factors in control of covid–19 pandemic–preliminary results. Retrieved August 21, 2021, from https://www.preprints.org/manuscript/202005.0036/download/final_file.
Jarynowski, A., Wójta–Kempa, M., Płatek, D., & Czopek, K. (2020). Attempt to understand public health relevant social dimensions of Covid–19 outbreak in Poland. Society Register, 4(3), 7–44. https://doi.org/10.14746/sr.2020.4.3.01
Jarynowski, A., Wójta–Kempa, M., Płatek, D., Krzowski, Ł., & Belik, V. (2020). Mobilność jako kluczowa zmienna wyjaśniającą regionalne różnice w dynamice zakażeń–wyniki wstępne [Spatial Diversity of COVID–19 Cases in Poland Explained by Mobility Patterns – Preliminary Results]. Retrieved August 21, 2021, from https://depot.ceon.pl/handle/123456789/18444.
Jarynowski A, (2021). Phenomenon of participatory “guerilla” epidemiology in postcommunist European countries. Baltic Rim Economies 3. Retrieved August 21, 2021, from https://sites.utu.fi /bre/phenomenon-of-participatory-guerilla-epidemiologyin-post-communist-european-countries/.
Jasiński, M. (2020). Prognozy rozwoju epidemii koronawirusa [Predictions of coronavirus epidemic]. Retrieved August 21, 2021, from http://www.fi zykwyjasnia.pl/na-biezaco/prognozy-rozwoju-epidemii-koronawirusa/.
Jia, J. S., Lu, X., Yuan, Y., Xu, G., Jia, J., & Christakis, N. A. (2020). Population flow drives spatio–temporal distribution of Covid–19 in China. Nature, 582(7812), 389–394. https://doi.org/10.1038/s41586-020-2284-y
Kędzierski, M., Oramus, M. (2021). Sanepid w ogniu. Ewolucja funkcjonowania Państwowej Inspekcji Sanitarnej w czasie pandemii COVID–19 [Sanitary Ispection on fi re. Evolution of the functioning of the State Sanitary Inspection during the COVID–19 pandemic].
Retrieved August 21, 2021, from https://uek.krakow.pl/artykuly/nauka/raportsanepid-w-ogniu-ewolucja-funkcjonowania-panstwowej-inspekcji-sanitarnej-w-czasie-pandemii-covid-19.
Killeen, B. D., Wu, J. Y., Shah, K., Zapaishchykova, A., Nikutta, P., Tamhane, A., . . ., et al. (2020). A county–level dataset for informing the United States’ response to Covid–19. arXiv preprint :2004.00756.
Kovacs, R., Dunaiski, M., & Tukiainen, J. (2020). Compulsory face mask policies do not affect community mobility in Germany. Available at SSRN 3620070.
Kowalski, P., & Konior, A. (2020). Zachorowalność na covid–19 w regionach ze zwiększonym zanieczyszczeniem powietrza [Covid–19 severity due to the polluted air]. Retrieved August 21, 2021, from https://airly.org/pl/zachorowalnosc-na-covid-19-w-regionach-ze-zwiekszonym-zanieczyszczeniem-powietrza/.
Kowalski, P. A., Szwagrzyk, M., Kielpinska, J., Konior, A., & Kusy, M. (2021). Numerical analysis of factors, pace and intensity of the corona virus (COVID–19) epidemic in
Poland. Ecological informatics, 63, 101284. https://doi.org/10.1016/j.ecoinf.2021.101284
Krueger, T., et al. (2020a). Epidemia covid–19: Analiza sytuacji bieżącej i prognozy krótkoterminowe, czerwiec [The covid–19 epidemic: Analysis of the current situation and short–term forecasts, June]. Retrieved August 21, 2021, from https://mocos.pl/images/
reports/20200604/wroclaw/report_wroclaw_20200604.pdf.
Krueger, T., et al. (2020b). Epidemia covid–19: Analiza sytuacji bieżącej i prognozy krótkoterminowe, maj [The covid–19 epidemic: Analysis of the current situation and short–term forecasts, Mai]. Retrieved August 21, 2021, from https://mocos.pl/images/reports/20200513/wroclaw/report_wroclaw_20200513.pdf.
Krzowski, L., & Trzos, A. (2020). Prewencja zachorowań, triage, zarządzanie i wstępna diagnostyka Covid–19 [Prevention of disease, triage, management and preliminary diagnostic of COVID–19]. Na ratunek, 2(2). 22–34.
Krzysztofi k, R., Kantor–Pietraga, I., & Spórna, T. (2021). Multidimensional Conditions of the First Wave of the COVID–19 Epidemic in the Trans–Industrial Region. An Example of the Silesian Voivodeship in Poland. Sustainability, 13(8), 4109. https://doi.
org/10.3390/su13084109
Łowicki, D. (2019). Variability of the particulate matter air pollution of Polish cities with a prediction until 2020. Geographia Polonica, 92(2), 161–171. https://doi.org/10.7163/GPol.0142
Maier, B. F., & Brockmann, D. (2020). Effective containment explains subexponential growth in recent confi rmed COVID–19 cases in China. Science, 368(6492), 742–746. https://doi.org/10.1126/science.abb4557
Mense, A., & Michelsen, C. (2020). Pendlerverflechtungen haben starken einfl uss auf die verbreitung des corona–virus [Commuter connections have a strong infl uence on the spread of the coronavirus]. Retrieved August 21, 2021, from https://www.diw.de/de/diw_01.c.790305.de/publikationen/diw_aktuell/2020_0043/pendlerverflechtungen_haben_starken_einfluss_auf_die_verbreitung_des_corona–virus.html.
Messner, W., & Payson, S. E. (2020). The infl uence of contextual factors on the initial phases of the Covid–19 outbreak across us counties. medRxiv. https://doi.org/10.1101/2020.05.13.20101030
Miles, D., Stedman, M., & Heald, A. (2020). Living with Covid–19: balancing costs against benefi ts in the face of the virus. National Institute Economic Review, 253, R60–R76. https://doi.org/10.1017/nie.2020.30
Ministerstwo Finansów. (2020). Budżet na 2021 [Financial plan for 2021]. Retrieved August 21, 2021, from https://www.gov.pl/web/fi nanse/szacunek-2020.
Mostowy, R. (2020). Analiza pandemii Covid–19 w polsce w czasie rzeczywistym [Analysis of COVID–19 pandemic in real time]. Retrieved August 21, 2021, from https://rmostowy.github.io/covid-19/czas-rzeczywisty/.
Mueller, B. (2020). Contact tracing, key to reining in the virus, falls flat in the west. Retrieved August 21, 2021, from https://www.nytimes.com/2020/10/03/world/europe/covid-contract-tracing.html.
Nowak, M.J. (2021). Polityka przestrzenna w czasie kryzysu [Spatial policy during the crisis]. Warszawa: Wydawnictwo Naukowe Scholar.
Ochab–Marciniak, A. (2020). Koronawirus statystyki aom. [Coronavirus: statistics by AOM] Retrieved August 21, 2021, from http://soft.ichf.edu.pl/ochab/coronavirus_poland/2020.04.08/koronawirus_statystyki.2020.04.08.html.
Paradowski, M. B., Jarynowski, A., Czopek, K., & Jelinska, M. (2020). Peer interactions and second language learning: The contributions of social network analysis in immersion/study abroad vs at–home environments–preprint. Retrieved August 21, 2021, from http://interdisciplinary-research.eu/wp-content/uploads/2020/05/paradowski-1.pdf.
Pinkas, J., Jankowski, M., Szumowski, Ł., Lusawa, A., Zgliczyński, W. S., Raciborski, F., ... & Gujski, M. (2020). Public health interventions to mitigate early spread of SARS–CoV–2 in Poland. Medical science monitor: international medical journal of experimental and clinical research, 26, e924730–1. https://doi.org/10.12659/msm.924730
PKW. (2020). Wyniki głosowania na listy procentowo w powiatach w wyborach do parlamentu europejskiego [Results of voting for lists as a percentage in poviats in elections to the European parliament] . Retrieved August 21, 2021, from https://pe2019.pkw.gov.pl/pe2019/pl/dane_w_arkuszach.
Polski Instytut Ekonomiczny. (2020). Pandenomics – zestaw narzędzi fi skalnych i monetarnych w dobie kryzysów [Pandenomics – a set of fiscal and monetary tools in times of crises]. Retrieved August 21, 2021, from http://pie.net.pl/wp-content/
uploads/2020/04/PIE-Pandenomics.pdf.
Pullano, G., Valdano, E., Scarpa, N., Rubrichi, S., & Colizza, V. (2020). Evaluating the effect of demographic factors, socioeconomic factors, and risk aversion on mobility during the COVID–19 epidemic in France under lockdown: a population–based study. The Lancet Digital Health, 2(12), e638–e649. https://doi.org/10.1016/s2589-7500(20)30243-0
Pybus, O. (2020). Preliminary analysis of SARS–CoV–2 importation and establishment of UK
transmission lineages. Retrieved August 21, 2021, from https://virological.org/t/preliminary-analysis-of-sars-cov-2-importation-establishment-of-uk-transmission-lineages/507.
Raciborski, F., Pinkas, J., Jankowski, M., Sierpinski, R., Zgliczynski, W., Szumowski, Ł., . . . Gujski, M. (2020). Dynamics of Covid–19 outbreak in Poland: an epidemiological analysis of the first two months of the epidemic. Pol. Arch. Intern. Med, 130, 615–621.
https://doi.org/10.20452/pamw.15430
Rakowski, F. (2020). Predicting the course of the Covid–19 epidemic in Poland. Retrieved August 21, 2021, from https://www.youtube.com/watch?v=Q00VrIZ69RY.
Rogalski, M. (2020). Covid–19 według powiatów [Covid–19 in poviats]. Retrieved August 21, 2021, from https://docs.google.com/spreadsheets/d/1Tv6jKMUYdK6ws6SxxAsHVxZbglZfi sC8x_HZ1jacmBM/.
Rosiński, J., Rózanska, A., Jarynowski, A., Wójkowska–Mach, J., et al. (2019). Factors shaping attitudes of medical staff towards acceptance of the standard precautions.
International journal of environmental research and public health, 16(6), 1050. https://doi.org/10.3390/ijerph16061050
Sannigrahi, S., Pilla, F., Basu, B., & Basu, A. S. (2020). The overall mortality caused by Covid–19 in the European region is highly associated with demographic composition: A spatial regression–based approach. arXiv preprint:2005.04029.
Selectivv. (2020). Sytuacja podczas covid–19 na podstawie danych z mobile [Situation during covid–19 based on mobile data]. Retrieved August 21, 2021, from https://selectivv.com/sytuacja-podczas-covid-19-na-podstawie-danychz-mobile/ .
Singh, L., Bansal, S., Bode, L., Budak, C., Chi, G., Kawintiranon, K., . . . Wang, Y. (2020).
A first look at Covid–19 information and misinformation sharing on Twitter. arXiv preprint:2003.13907.
Sitek, S., Pytel, S., & Zuzańska–Zysko, E. (2020). Rozmieszczenie i zasięg występowania sars–cov–2 w województwie śląskim [Distribution and spread of SARS–CoV–2 in the Silesian Voivodeship]. Retrieved August 21, 2021, from https://us.edu.pl/prof-ssitek-prof-s-pytel-prof-e-zuzanskazysko-rozmieszczenie-i-zasieg-wystepowania-sarscov-2-w-wojewodztwie-slaskim/.
Śleszyński, P. (2018). Polska średnich Miast: Założenia i Koncepcja Deglomeracji w Polsce
[Poland of Medium–sized Cities: Assumptions and Concept of Deglomeration in Poland ]. Klub Jagielloński. Retrieved August 21, 2021, from https://klubjagiellonski.pl/publikacje/polska–srednich-miast-zalozenia-i-koncepcja-deglomeracji-w-polsce/
Śleszyński, P. (2020). Geografia koronawirusa w Polsce [The geography of the coronavirus in Poland]. Retrieved August 21, 2021, from https://ptgeo.org.pl/2020/06/geografi a-koronawirusa-w-polsce/.
Śleszyński, P. (2021). Wpływ pandemii COVID–19 na przestrzenne struktury demograficzne i osadnicze Polski [The impact of the COVID–19 pandemic on the spatial demographic and settlement structures of Poland]. (private correspondence)
StatSoft. (2020). Statystyczna analiza zachorowań na koronawirusa w polsce [Statistical analysis
of coronavirus cases in Poland]. Retrieved August 21, 2021, from https://www.statsoft.pl/systemy-data-mining/statystyczna-analiza-zachorowan-na-koronawirusa-w-polsce/.
Su, D., Chen, Y., He, K., Zhang, T., Tan, M., Zhang, Y., & Zhang, X. (2020). Influence of socio–ecological factors on Covid–19 risk: a cross–sectional study based on 178 countries/regions worldwide. Regions Worldwide. Retrieved August 21, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7276015/.
Szmuda, T., et al. (2020). Datasets and future research suggestions concerning SARS–CoV–2. Eur J Transl Clin Med, 3(2), 80–85. https://doi.org/10.31373/ejtcm/124734
Tarnowski, P. (2020). Wizualizacje dla powiatów [Visualization for poviats]. Retrieved August 21, 2021, from https://public.tableau.com/profile/piotrekt#!/vizhome/covid19_powiaty/covid19Podzianapowiat.
Trzos, A., Krzowski, Ł., & Długosz, K. (2017). Specyfi ka działań ratownictwa medycznego [The specifi city of emergency medical services]. Na Ratunek, 4, 17.
UWM. (2020). Poland coronavirus data. Retrieved August 21, 2021, from https://github.com/dtandev/coronavirus.
Wójta–Kempa, M., & Jarynowski, A. (2020). Ocena poziomu poinformowania na temat przebiegu i skutków pandemii covid–19 [Assessment of the level of information on the course and consequences of the covid–19 pandemic]. Retrieved August 21, 2021, from
https://drive.google.com/fi le/d/1WijPJLCGEmEwaJfo6e8ZudvamNn0_D3K/.
WSSElubuskie. (2020). Wydatki jednostek budżetowych [Expenditure of budgetary units]. Retrieved August 21, 2021, from https://shorturl.at/rwEFZ.
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