IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v22y2025i4p545-d1626618.html
   My bibliography  Save this article

Spatial Analysis of Tuberculosis, COVID-19, and Tuberculosis/COVID-19 Coinfection in Recife, PE, Brazil

Author

Listed:
  • Alene Bezerra Araújo Silva

    (Graduate Program in Health Sciences, Faculty of Medical Sciences, University of Pernambuco, Recife CEP 50100-010, PE, Brazil)

  • Wayner Vieira de Souza

    (Department of Public Health, Aggeu Magalhães Research Center, Fiocruz, Recife CEP 50.740-465, PE, Brazil)

  • José Constantino Silveira Júnior

    (Aggeu Magalhães Research Center, Fiocruz, Recife CEP 50.740-465, PE, Brazil)

  • Juliana Silva de Santana

    (Applied Cellular and Molecular Biology, University of Pernambuco, Recife CEP 50100-010, PE, Brazil)

  • Ricardo Arraes de Alencar Ximenes

    (Department of Tropical Medicine, Federal University of Pernambuco, Recife CEP 50670-901, PE, Brazil
    Department of Medical Clinic, University of Pernambuco, Recife CEP 50100-010, PE, Brazil)

Abstract

Tuberculosis (TB) remains a public health problem, which the COVID-19 pandemic may have exacerbated. Scaling TB, COVID-19, and coinfection in area and socioeconomic contexts is an important way to detect more vulnerable groups. Objective: To verify, through the spatial distribution of cases of tuberculosis, COVID-19, and coinfection, the existence of an association between the risk of illness and income. Methods: An analytical ecological study was carried out in Recife, whose unit of analysis was the neighborhood, in the year 2020. The data were collected from the SINAN-TB, NOTIFICA-PE, and IBGE Information Systems. Neighborhoods were grouped into strata according to income through K-means analysis. Incidence rates were calculated. Marshall’s Local Empirical Bayesian Smoothing Method was used. Risk ratios were calculated to estimate the magnitude of association between income strata and incidence rates. Results: A heterogeneous pattern of spatial distribution was verified for the three events addressed, compatible with the inequality of income distribution existing in Recife. For COVID-19, the highest incidence rates occurred in the strata of better-income neighborhoods. There was an association with a gradual increase in the incidence rate as income decreased for tuberculosis. Coinfection did not show a gradual increase in the incidence rate as income decreased, but a lower incidence rate was observed in the stratum of better economic conditions. Conclusions: Studies must be carried out to verify the spatial distribution of COVID-19 and its possible association with socioeconomic factors in subsequent years. There was a positive association between low income and the risk of becoming ill from tuberculosis. The lower incidence rate of coinfection in the stratum of the higher-income population suggests that the pre-existence of TB contributes to illness by COVID-19 in the low-income population.

Suggested Citation

  • Alene Bezerra Araújo Silva & Wayner Vieira de Souza & José Constantino Silveira Júnior & Juliana Silva de Santana & Ricardo Arraes de Alencar Ximenes, 2025. "Spatial Analysis of Tuberculosis, COVID-19, and Tuberculosis/COVID-19 Coinfection in Recife, PE, Brazil," IJERPH, MDPI, vol. 22(4), pages 1-13, April.
    • Handle: RePEc:gam:jijerp:v:22:y:2025:i:4:p:545-:d:1626618
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/22/4/545/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/22/4/545/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Munazza Fatima & Kara J. O’Keefe & Wenjia Wei & Sana Arshad & Oliver Gruebner, 2021. "Geospatial Analysis of COVID-19: A Scoping Review," IJERPH, MDPI, vol. 18(5), pages 1-14, February.
    2. Wentao Yang & Min Deng & Chaokui Li & Jincai Huang, 2020. "Spatio-Temporal Patterns of the 2019-nCoV Epidemic at the County Level in Hubei Province, China," IJERPH, MDPI, vol. 17(7), pages 1-11, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Melissa Silva & Iuria Betco & César Capinha & Rita Roquette & Cláudia M. Viana & Jorge Rocha, 2022. "Spatiotemporal Dynamics of COVID-19 Infections in Mainland Portugal," Sustainability, MDPI, vol. 14(16), pages 1-28, August.
    2. Rastko Jovanović & Miloš Davidović & Ivan Lazović & Maja Jovanović & Milena Jovašević-Stojanović, 2021. "Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    3. Xin Li & Peixin Lu & Lianting Hu & Tianhui Huang & Long Lu, 2020. "Factors Associated with Mental Health Results among Workers with Income Losses Exposed to COVID-19 in China," IJERPH, MDPI, vol. 17(15), pages 1-11, August.
    4. Nelson Mileu & Nuno M. Costa & Eduarda M. Costa & André Alves, 2022. "Mobility and Dissemination of COVID-19 in Portugal: Correlations and Estimates from Google’s Mobility Data," Data, MDPI, vol. 7(8), pages 1-17, July.
    5. Qiushi Chen & Michiko Tsubaki & Yasuhiro Minami & Kazutoshi Fujibayashi & Tetsuro Yumoto & Junzo Kamei & Yuka Yamada & Hidenori Kominato & Hideki Oono & Toshio Naito, 2021. "Using Mobile Phone Data to Estimate the Relationship between Population Flow and Influenza Infection Pathways," IJERPH, MDPI, vol. 18(14), pages 1-32, July.
    6. Samuel O. M. Manda & Timotheus Darikwa & Tshifhiwa Nkwenika & Robert Bergquist, 2021. "A Spatial Analysis of COVID-19 in African Countries: Evaluating the Effects of Socio-Economic Vulnerabilities and Neighbouring," IJERPH, MDPI, vol. 18(20), pages 1-15, October.
    7. Rosina Moreno & Esther Vayá, 2023. ""Geographical distribution of the COVID-19 pandemic across waves in Spain"," IREA Working Papers 202301, University of Barcelona, Research Institute of Applied Economics, revised Jan 2023.
    8. Pavlov, Konstantin & Timiryanova, Venera & Yusupov, Kasim & Krasnoselskaya, Dina, 2022. "Анализ волн распространения Covid-19 в России [Analysis of Covid-19 wave distribution in Russia]," MPRA Paper 114637, University Library of Munich, Germany.
    9. Boris Kauhl & Jörg König & Sandra Wolf, 2023. "Spatial Distribution of COVID-19 Hospitalizations and Associated Risk Factors in Health Insurance Data Using Bayesian Spatial Modelling," IJERPH, MDPI, vol. 20(5), pages 1-10, February.
    10. Mohd Sahrul Syukri Yahya & Edie Ezwan Mohd Safian & Burhaida Burhan, 2020. "The Real-Time Situation of Covid-19 Pandemic between MCO, CMCO and RMCO Using Geographic Information System (GIS): Study Case in Malaysia," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 4(10), pages 75-81, October.
    11. František Petrovič & Katarína Vilinová & Radovan Hilbert, 2021. "Analysis of Hazard Rate of Municipalities in Slovakia in Terms of COVID-19," IJERPH, MDPI, vol. 18(17), pages 1-12, August.
    12. Sylwia Krzysztofowicz & Katarzyna Osińska-Skotak, 2021. "The Use of GIS Technology to Optimize COVID-19 Vaccine Distribution: A Case Study of the City of Warsaw, Poland," IJERPH, MDPI, vol. 18(11), pages 1-22, May.
    13. Nushrat Nazia & Zahid Ahmad Butt & Melanie Lyn Bedard & Wang-Choi Tang & Hibah Sehar & Jane Law, 2022. "Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review," IJERPH, MDPI, vol. 19(14), pages 1-28, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:22:y:2025:i:4:p:545-:d:1626618. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.