https://orcid.org/0000-0002-9181-344X
Figures
Abstract
Objective
Using spatial analysis techniques, this study investigates the associations between socioeconomic indicators measured at the census tract level and the incidence of Zika virus (ZIKV) infection in pregnant persons and microcephaly in newborns in Recife, Pernambuco, Brazil, from 2015 to 2021.
Methods
In this ecological study, data on cases of ZIKV infections among pregnant persons registered in the Brazilian Information System for Notifiable Diseases (Sistema de Informação de Agravos de Notificaçao, SINAN-Zika) and cases of microcephaly among live births registered in the Public Health Event Registration System (Registro de Eventos em Saúde Pública, RESP-Microcefalia) and the Live Birth Information System (Sistema de Informações Sobre Nascidos Vivos, SINASC) were georeferenced based on residential address and aggregated within census tracts. Spatial autocorrelation was performed using the bivariate global and local Moran’s I indices, which considered the incidence rates of maternal ZIKV infections and microcephaly during the epidemic (2015–2017) and post-epidemic (2018–2021) time periods in relation to each other as well as social, economic, sanitation, and urban infrastructure covariates derived from the 2010 census.
Results
From 2015 to 2021, the city of Recife registered 253 cases (n = 240 in 2015–2017 and n = 13 in 2018–2021) of ZIKV infection in pregnant persons and 147 cases (n = 137 in 2015–2017 and n = 10 in 2018–2021) of microcephaly in newborns. The global bivariate Moran’s I index between the incidences of ZIKV infection in pregnant persons and microcephaly were 0.127 (p = 0.001) in 2015–2017 and 0.074 (p = 0.002) in 2018–2021, indicating a positive spatial correlation, as higher was the ZIKV infection in pregnant persons, higher was the incidence of microcephaly. Furthermore, incidences of maternal ZIKV infection and microcephaly were consistently associated with indicators of greater social vulnerability and economic deprivation at the census tract level.
Conclusion
During the epidemic and post-epidemic periods in Recife, cases of ZIKV in pregnant persons and microcephaly were concentrated in census tracts with relatively higher socioeconomic vulnerability, reinforcing the need for research to inform the development of social protection and environmental policies to mitigate ZIKV-related risks.
Author summary
When cities lack proper planning, land use becomes disorganized, which creates ideal conditions for mosquitoes to thrive and spread diseases — especially affecting poorer communities. This study looked at how social and economic factors are connected to Zika virus infections in pregnant women and cases of microcephaly in babies in Recife, Brazil, between 2015 and 2021. The results showed that areas with higher poverty had more cases of Zika in pregnant women and more babies born with microcephaly. This highlights the strong link between social inequality and health problems. Both during and after the Zika outbreak, these issues continued to affect the most vulnerable neighborhoods in the city. These findings show how important it is to invest in public policies that improve living conditions and protect people socially and environmentally. Such actions are key to reducing the risk of Zika and other similar diseases, especially in the communities that need the most support.
Citation: Lucena Sá ACdC, Oliveira ALSd, Miranda-Filho DdB, Martelli CMT, Araújo TVBd, Brickley EB, et al. (2025) Mapping the risk of Zika virus infections in pregnant persons and microcephaly in newborns in relation to socioeconomic indicators in Recife, Pernambuco, Brazil: A spatial analysis (2015 to 2021). PLoS Negl Trop Dis 19(7): e0013240. https://doi.org/10.1371/journal.pntd.0013240
Editor: Amy C. Morrison, University of California Davis School of Veterinary Medicine, UNITED STATES OF AMERICA
Received: September 18, 2024; Accepted: June 13, 2025; Published: July 9, 2025
Copyright: © 2025 Lucena Sá et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are included within the manuscript, encompassing the absolute data used for statistical calculations. Individual participant data are protected due to ethical considerations. In accordance with the standards for good clinical research of the HUOC/Procape Hospital Complex Ethics Committee, data cannot be shared publicly because the dataset contains sensitive human subject data. Participants did not provide consent for public sharing of their data, and public availability would compromise patient privacy. De-identified data can made available upon reasonable request from qualified investigators by contacting email address ppg.cienciasdasaude@upe.br.
Funding: This study recieved support from the sources as listed below: The European Union’s Horizon 2020 Research and Innovation program (https://ec.europa.eu/programmes/horizon2020/Accessed 10 June 2021) under the ZikaPLAN Grant Agreement (Nr. 734584) for RAAX, (https://Zikaplan.tghn.org/Accessed June 10, 2021); Wellcome Trust and the UK Department for International Development (201870 / Z / 16 / Z and 205377 / Z / 16 / Z for DBMF; https://wellcome.ac.uk/Accessed 10 June 2021); Wellcome Trust – Research Enrichment in Epidemic Situations (107779/Z/15/Z; ER1505 for DBMF and ER1601 for RAAX); Medical Research Council on behalf of the Newton Fund and Wellcome Trust (MC_PC_15088; https://mrc.ukri.org/Accessed 10 June 2021) for RAAX; US National Institute of Child Health and Human Development (NICHD), National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Environmental Health Sciences (NIEHS), and Oswaldo Cruz-Fiocruz Foundation, Brazil (for the Cohort Study International Prospective Observational on Zika in Infants and Pregnancy—ZIP Study), grant number: HHSN275201800001I for RAAX; Brazilian Ministry of Health, Pan American Health Organization and Improvement of Research Activity in Epidemic Situations (for CMTM - MERG Case Control Study); Foundation for Support to Science and Technology of PE—FACEPE (APQ-0192–4.01 / 17 for Postgraduate Program in Health Sciences-UPE and APQ-0172–4.01/16 for DBMF; http://www.facepe.br/Accessed on July 20, 2021); Coordination for the Improvement of Higher Education Personnel—Brazil (CAPES)—Financial Code 001; Scholarship holder: National Council for Scientifc and Technological Development (309722 / 2017–9 and 312626_2021-5 to RAAX, 306708 / 2014–0 to CMTM; http://www.cnpq.br/Accessed on July 20, 2021); Health Surveillance Secretariat / Brazilian Ministry of Health Public Health Emergency Response — Zika virus and Microcephaly (837058/2016 for RAAX); National Council for Scientifc and Technological Development, Coordination for the Improvement of Higher Education Personnel (http://www.capes.gov.br/Accessed on June 10, 2021); Department of Science and Technology (http://rebrats.saude.gov.br/noticias/59Accessed on July 20, 2021) Accessed on June 20, 2021 for the Prevention and Combat of Zika Virus I (440839 / 2016–5 for RAAX). Wellcome Collaborative Award entitled “Long-term consequences of Zika virus infections during pregnancy for school-aged children and their families in Brazil”. Ref: 224494/B/21/Z for RAAX. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Zika virus (ZIKV) is an arthropod-borne virus (arbovirus) belonging to the Orthoflavivirus genus of the Flaviviridae family [1,2]. In urban settings, ZIKV is primarily transmitted by the bite of Aedes aegypti mosquitoes, which are also vectors for dengue, chikungunya, yellow fever, and other viruses [3,4]. ZIKV infections during pregnancy can have adverse consequences for fetal and postnatal development and have, therefore, become a cause for concern, particularly for families planning to conceive and individuals who are pregnant [5,6].
After the emergence of an epidemic of an exanthematous disease in Brazil [7] which was confirmed in April 2015 to be the beginning of an explosive outbreak of ZIKV [8] and the subsequent detection of a cluster of microcephaly cases in October 2015 [9], national and international health authorities escalated operational surveillance measures, particularly focusing on ZIKV infections among pregnant individuals and microcephaly among newborns [10,11]. Although microcephaly (i.e., an abnormally small head circumference) can be caused by various factors (e.g., genetics, harmful substances, malnutrition) or have undefined etiology (i.e., idiopathic) [12], robust evidence has now confirmed the association between ZIKV infection during pregnancy and the development of microcephaly [13]. In addition, prenatal exposure to ZIKV has been associated with a range of outcomes including central nervous system damage including brain calcifications and ventriculomegaly, ocular anomalies, deafness, arthrogryposis, dysphagia, epilepsy, and delays in neurodevelopment – collectively recognized as Congenital Zika Syndrome (CZS) [3,6,14].
In many Brazilian cities, urbanization and population growth have resulted in sprawling, unplanned expansions of urban areas often lacking basic infrastructure, including adequate sanitation, access to clean drinking water, and environmental management [15]. This lack of structural planning leads to a chaotic, irregular occupation of space, which fosters the proliferation of mosquitoes and spread of infectious disease, with disproportionate impacts for the poorest segment of the population. Previous studies from the Brazilian cities of Rio de Janeiro [16–18] and Goiânia [19] have provided evidence of a higher frequency of ZIKV infections and CZS in more socioeconomically deprived areas. Similarly, a 2022 systematic review provided evidence of an association between indicators of lower socioeconomic position (e.g., lower education) and arboviral infection risks [20].
The hypothesis of the present study is that the distribution of ZIKV cases in pregnant women and microcephaly in newborns in the city of Recife is not homogeneous and is determined by the socioeconomic conditions of the environment. Using electronic health records collected between 2015–2021 in the city of Recife in the northeastern state of Pernambuco, which registered the highest number of cases in Brazil for 2016 [10,21], this study aims to understand the spatial distribution of ZIKV infections during pregnancy and live births with microcephaly and their associations with socioeconomic factors measured at the ecological level. This study will highlight spatial disparities in risk and identify census tracts that should be targeted for interventions to control mosquito vectors and reduce ZIKV transmission.
Methods
Ethics statement
The research was approved by the Ethics Committee of the HUOC/PROCAPE Hospital Complex, under CAAE No. 63869322.5.0000.5192 with approval report No. 5,738,832. This study did not require individual consent, as it was a study using secondary databases made available by the Pernambuco State Department of Health and the Recife Municipal Health Department, and followed the ethical procedures recommended for this type of study by Resolution MS/CNS 466/2012.
Study design and data sources
This ecological study was conducted in Recife, the state capital of Pernambuco, Brazil, using the census tract as the spatial unit of analysis. The municipality of Recife is divided into 8 Health Districts, 94 official neighborhoods, and 1854 census tracts (based on the 2010 census). The population of Recife in 2022 (i.e., the time of the most recently available census data) was reported to be 1,488,920 inhabitants distributed across an area of 218,843 km2, resulting in a demographic density of 6,803.6 inhabitants/km2 [22].
This study analyzed administrative data collected between April 2015 and December 2021 from: (i) all pregnant persons registered as ZIKV-positive in the Brazilian Information System for Notifiable Diseases (Sistema de Informação de Agravos de Notificaçao, SINAN-Zika). ZIKV-positive in pregnant persons was confirmed when they presented pruritic maculopapular rash accompanied by two or more of the following signs and symptoms: fever, conjunctival hyperemia without secretion and pruritus, polyarthralgia, and periarticular edema. A suspected case was considered for ZIKV diagnosis if it tested positive on one of the following specific diagnostic methods: viral isolation, detection of viral RNA by reverse transcription polymerase chain reaction (RT-PCR), or IgM serology [23]. (ii) All live births diagnosed with microcephaly due to congenital ZIKV infection registered on the Public Health Event Registration System (Registro de Eventos em Saúde Pública, RESP-Microcefalia) and the Live Birth Information System (Sistema de Informações Sobre Nascidos Vivos, SINASC). Microcephaly cases were classified based on imaging and laboratory evidence. Cases were confirmed by imaging alone if the newborn presents with radiological findings suggestive of congenital infection, even in the absence of laboratory results. Laboratory-confirmed cases include those with microcephaly and a definitive diagnosis of either TORCH infections (syphilis, toxoplasmosis, rubella, cytomegalovirus, or herpes simplex) or Zika virus (ZIKV), based on conclusive laboratory testing of maternal and/or neonatal samples. In addition, microcephaly cases were confirmed when a newborn’s head circumference was ≤ 2 standard deviations below the mean for sex and gestational age according to the INTERGROWTH-21st growth curve used by the World Health Organization (WHO) and the Brazilian Ministry of Health [13,23]. Cases of microcephaly among stillbirths were not included in this study, as they are not recorded in SINASC. In addition, during the study period, only two stillbirths were reported in the Brazilian Mortality System (Sistema de Informações sobre Mortalidade, SIM), and their residential addresses were not registered in the system.
Database linkage
First, both databases were standardized by removing duplicate entries. Subsequently, a probabilistic record linkage method was applied using a multi-step routine, where each step employed a specific blocking key. The next stage involved linking the datasets through the blocking process and record matching.
As comparison fields, the newborn’s full name and age were used, with linkage parameters estimated through the application of Expectation-Maximization (EM) algorithms. These parameters were then employed to calculate scores for the links established in each blocking step.
Finally, a single final dataset was generated, containing the true pairs identified based on the linkage score and manual review. The software Reclink III (version 3.1.6) and Microsoft Excel were used for this process.
Georeferencing and variables
Cases of ZIKV infection in pregnant persons and microcephaly in live births were georeferenced using the residential address contained in the SINAN-Zika and RESP-Microcephalia/SINASC databases respectively, using the automatic tool MMQGIS/Geocode, which provides the geographic latitude and longitude coordinates of each address. The Google Maps/Open Street Map database was used as a reference integrated into QGIS 3.34. Subsequently, the specific georeferenced data were added to the census tract grid, thus preserving the location of the individual’s address.
Cases that could not be automatically located using the MMQGIS/Geocode tool were manually georeferenced, which involved searching for each address on the Recife City Hall spatial database and the postal system’s website. The digital cartographic base of the census tracts in the city of Recife were provided by the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatistica, IBGE) website (www.ibge.gov.br) in shapefile format, available to free download in https://www.ibge.gov.br/geociencias/downloads-geociencias.html.
The primary study outcomes (i.e., the dependent variables) were the mean annual incidences of ZIKV infections among pregnant persons and microcephaly among live births. The mean annual incidence of ZIKV infections among pregnant persons was calculated, for each year, as the number of ZIKV cases in pregnant persons divided by the population of live births (as a proxy for the number of pregnant individuals) in the census tract and multiplied by one thousand pregnant persons. The mean annual incidence of microcephaly was calculated, for each year, as the number of cases of microcephaly divided by the population of live births in the census tract, multiplied by a thousand live births. Since there was a possible random fluctuation of the outcomes, the incidences were smoothed using the local empirical Bayes method [24,25]. To compare the spatial distribution of the study outcomes longitudinally, thematic maps were generated within two-time frames: from 2015 to 2017 during the epidemic period in Brazil and from 2018 to 2021 during the post-epidemic period in Brazil. All data were analyzed using QGIS 3.26 and GeoDa 1.8.
The exposure (i.e., independent) variables investigated social, economic, sanitation and urban infrastructure at the census tract level as recorded in the 2010 IBGE database. Specifically, these variables included: (i) the proportion of households with a nominal monthly household income per capita ≤1 minimum wage (i.e., 510 BRL, approximately 290 USD in 2010); (ii) the proportion of households with a water supply other than that supplied via the main distribution network (i.e., via a well or spring, rainwater stored in cisterns, or other sources); (iii) the proportion of households linked to a sewage system via the main sewage or rainwater network; (iv) the proportion of households with no bathroom; (v) the proportion of households with inappropriate waste disposal (i.e., burned or buried on the property, thrown onto vacant land or street, thrown into a river, lake or sea or other destinations); (vi) the proportion of households with inappropriate sewage disposal; (vii) the proportion of households with accumulated garbage on the streets; (viii) the proportion of households with electricity; (ix) the proportion of racially minoritized (i.e., Preta [Black] and Parda [Brown/mixed race]) women aged >10 years; and (x) the proportion of illiterate women aged over 10 years.
Spatial analysis
For the spatial analysis, the bivariate global Moran’s I was first calculated between the incidences of ZIKV infections among pregnant persons and microcephaly among live births during the two time periods (i.e., 2015–2017 and 2018–2021). It tests the spatial dependence among observations. I > 0 indicates direct correlation (clustering) between neighbors. When I < 0, indicate negative or inverse correlations (i.e., dispersion). And when I = 0, there is no spatial autocorrelation [24]. Positive spatial autocorrelation indicates that areas with higher proportions of the independent variable (i.e., socioeconomic indicator) tend to cluster with higher incidences of the outcome (i.e., ZIKV infection in pregnant persons or microcephaly), while negative autocorrelation suggests an inverse relationship.
To visualize the spatial distribution of census tracts with clusters of risks of ZIKV infections in pregnant persons and microcephaly, LISA Maps were generated for each of the time periods. This allows the detection of census tracts with spatial dependencies that are not illustrated through global indices. Two types of maps were used in the Moran autocorrelation test: i) a BoxMap map showing clusters with high–high patterns (i.e., areas where a specific census tract and its neighbors show high values), low-low patterns (i.e., areas where a specific census tract and its neighbors show low values), low-high patterns (i.e., areas where a specific census tract has a low value and its neighbors have a high value), and high-low patterns (i.e., areas where a specific census tract has a high value and its neighbors have a low value); (ii) a MoranMap map showing statistically significant high-high, low-low, low-high, and high-low clusters; indicating the magnitude of the p-value for each census tract, with statistical significance defined according to a two-sided threshold of p < 0.05 [24].
Results
Sociodemographic characteristics
From 2015 to 2021, the city of Recife registered 253 cases (n = 240 in 2015–2017 and n = 13 in 2018–2021) of ZIKV infection in pregnant persons and 147 cases (n = 137 in 2015–2017 and n = 10 in 2018–2021) of microcephaly in newborns. The registered cases of pregnant persons infected with ZIKV infection were primarily aged between 21 and 30 years (43.9%, n = 111/253), identified as Parda (Brown) (71.2%, n = 131/184), and had between 10–12 years of schooling (55.5%, n = 101/182) (Table 1).
Among the 147 cases of microcephaly, these children were most frequently born to mothers who were aged between 21 and 30 years (49.3%, n = 71/143) and identified as Parda (Brown) (73.3%, n = 55/75). The majority of registered microcephalic newborns with available data were born at full-term (i.e., ≥ 37-weeks of gestational age; 86.3%, n = 120/139), were female (51.7%, n = 75/145), and had birth weight ≥ 2500g (80.1%, n = 113/141). The median (interquartile range) for birth length was 46 (45–47) cm (Table 2).
Bivariate spatial dependence of the incidence of ZIKV infection in pregnant persons and microcephaly
Analyzing the bivariate spatial dependence between the incidences of ZIKV infections in pregnant persons and microcephaly, the value of the global Moran’s I index were 0.127 (p = 0.001) for the period between 2015 and 2017 and 0.074 (p = 0.002) for the period between 2018 and 2021, thereby indicating the presence of spatial risk clusters in the two periods analyzed.
During the epidemic period from 2015 to 2017, 16.7% (n = 309/1854) of the census tracts were classified as both high risk for ZIKV infection in pregnant persons and high risk for microcephaly, while 53.0% (n = 983/1854) of the tracts were classified as low risk in both measures (Fig 1A). Considering the hypothesis of local spatial correlation for each census tracts, (Fig 1B), 19% of the census tracts presented a statistical significance (i.e., I ≠ 0 and p-value < 0.05). During the post-epidemic period from 2018 to 2021, the incidence of both measures decreased, and only 0.9% (n = 16/1854) of the census tracts were classified as both high risk for ZIKV infection in pregnant persons and high risk for microcephaly, while 91.8% of the tracts (n = 1702/1854) were classified as low risk in both measures.
Clusters areas in red (High-High) represent the region with the highest incidence of ZIKV infection in pregnant persons and higher incidence of microcephaly in each map: (Map A and B) period 2015-2017 and (Map C and D) period 2018-2021. The cartographic base that served as the basis for the production of the maps is at https://www.ibge.gov.br/geociencias/downloads-geociencias.html.
Considering the hypothesis of local spatial correlation for each census tracts, (Fig 1C), 9% of the census tracts presented a statistical significance (i.e., I ≠ 0 and p-value < 0.05).
By taking into account only the tracts that were high-risk for both ZIKV infections during pregnancy and microcephaly, high-risk clusters covering 119 tracts were identified in the north, central-west and south zones during the period from 2015 to 2017 (Fig 1B). During the period from 2018 to 2021, 14 tracts were considered high-risk clusters (Fig 1D).
Bivariate spatial correlation between the incidences of ZIKV infection in pregnant persons and microcephaly with socioeconomic indicators
According to the values of the global bivariate Moran’s I in Table 3, the incidence of both ZIKV infection in pregnant persons and microcephaly exhibited significant spatial autocorrelation for most variables studied across both analyzed periods. For example, positive spatial autocorrelation was observed between the proportion of households with a nominal monthly household income per capita ≤1 minimum wage and incidence of microcephaly (i.e., the higher the proportion of households with a nominal monthly household income per capita ≤1 minimum wage, the higher the incidence of microcephaly). While negative autocorrelation was observed between the the proportion of households linked to a sewage system via the main sewage or rainwater network and incidence of microcephaly (i.e., the lower the proportion of households with a nominal monthly household income per capita ≤1 minimum wage, the higher the incidence of microcephaly).
Spatial correlation between ZIKV incidence in pregnancy and socioeconomic indicators
By analyzing the Box Map and Moran Map with the bivariate spatial dependence between the incidence of ZIKV infection in pregnant persons and the covariates for the periods analyzed, the most vulnerable census tracts were highlighted (Fig 2). Among the independent variables that presented a positive correlation with the incidence of ZIKV infection in pregnant persons, the High-High standard tracts are classified as the areas of greatest vulnerability (i.e., low socioeconomic level) in relation to the risk of infection (high incidence of ZIKV in pregnant persons with a high proportion of the explanatory socioeconomic indicator variable). Among the variables that presented a negative autocorrelation with the event studied, the tracts that presented a High-Low pattern are the areas of greatest vulnerability (i.e., low socioeconomic level) in relation to the risk of infection, in this case, a high incidence of ZIKV in pregnant persons with a low proportion of the explanatory variable.
Clusters areas in red represent the region with highest incidence of ZIKV and higher vulnerability by socioeconomic variables in each map: (Map A and B) Proportion of households with a nominal monthly household income per capita of up to 1 minimum wage. (Map C and D) Proportion of households linked to a sewage system via the main sewage or rainwater network. (Map E and F) Proportion of households with no bathroom. (Map G and H) Proportion of households with accumulated garbage in public places. (Map I and J) Proportion of households with electricity. (Map L and M) Proportion of Black color/race (black and brown) women aged over 10 years. (Map N and O) Proportion of women aged over 10 years with low literacy skills. The cartographic base that served as the basis for the production of the maps is at https://www.ibge.gov.br/geociencias/downloads-geociencias.html.
Fig 2 presents the maps with the risk zones for ZIKV infection in pregnant persons, for each of the explanatory socioeconomic indicator variables, from 2015 to 2017, and Fig 3 from 2018 to 2021.
Clusters areas in red represent the region with the highest incidence of ZIKV and higher vulnerability by socioeconomic variables in each map: (Map A and B) Proportion of households with a nominal monthly household income per capita of up to 1 minimum wage. (Map C and D) Proportion of households linked to a sewage system via the main sewage or rainwater network. (Map E and F) Proportion of households with no bathroom. (Map G and H) Proportion of households with inappropriate waste disposal. (Map I and J) Proportion of households with an open sewage system in public areas. (Map L and M) Proportion of households with accumulated garbage in public places. (Map N and O) Proportion of Black color/race (black and brown) women aged over 10 years. (Map P and Q) Proportion of women aged over 10 years with low literacy skills. The cartographic base that served as the basis for the production of the maps is at https://www.ibge.gov.br/geociencias/downloads-geociencias.html.
Spatial correlation between the incidence of microcephaly and socioeconomic indicators
In Figs 4 and 5, the maps describe the risk zones of microcephaly, for each of the explanatory variables, in each of the periods. The maps indicate the tracts of greatest vulnerability in relation to the risk of a child living in that tract and developing microcephaly, given that the census tract has a high incidence of microcephaly with a high proportion of the explanatory variable. For example, the maps indicate a greater risk of microcephaly in tracts with a higher proportion of households with a nominal monthly household income per capita ≤1 minimum wage.
Clusters areas in red represent the region with the highest incidence of microcephaly and higher vulnerability by socioeconomic variables in each map: (Map A and B) Proportion of households with a nominal monthly household income per capita of up to 1 minimum wage. (Map C and D) Proportion of households linked to a sewage system via the main sewage or rainwater network. (Map E and F) Proportion of households with an open sewage system in public areas. (Map G and H) Proportion of households with electricity. (Map I and J) Proportion of Black color/race (black and brown) women aged over 10 years. (Map L and M) Proportion of women aged over 10 years with low literacy skills. The cartographic base that served as the basis for the production of the maps is at https://www.ibge.gov.br/geociencias/downloads-geociencias.html.
Clusters areas in red represent the region with the highest incidence of microcephaly and higher vulnerability by socioeconomic variables in each map: (Map A and B) Proportion of households with a nominal monthly household income per capita of up to 1 minimum wage. (Map C and D) Proportion of households with a water supply other than that supplied via the main distribution network. (Map E and F) Proportion of households with inappropriate waste disposal. (Map G and H) Proportion of households with an open sewage system in public areas. (Map I and J) Proportion of households with accumulated garbage in public places. (Map L and M) Proportion of Black color/race (black and brown) women aged over 10 years. (Map N and O) Proportion of women aged over 10 years with low literacy skills. The cartographic base that served as the basis for the production of the maps is at https://www.ibge.gov.br/geociencias/downloads-geociencias.html.
Discussion
Recife emerged as the epicenter of the ZIKV epidemic in Brazil, registering 253 confirmed cases of ZIKV infection among pregnant persons and 147 confirmed cases of microcephaly in newborns between 2015 and 2021. This ecological study has revealed a geographic pattern of spatial distribution, with confirmed cases of ZIKV in pregnant persons and microcephaly clustering in the north, central-west, southeast, and south zones of the municipality based on census tract data. Furthermore, this study has demonstrated that incidences of maternal ZIKV infection and microcephaly were consistently associated with indicators of greater social vulnerability and economic deprivation at the census tract level. It should be noted that the Moran’s index correlations remained consistent across the two analyzed periods, even with reduced ZIKV circulation in the post-epidemic period.
Our findings indicate the presence of spatial risk clusters, with an overlap in the areas experiencing increased incidences of maternal ZIKV infections and microcephaly. High-risk areas for ZIKV outcomes were concentrated in ‘pockets of poverty,’ even within wealthier neighborhoods. Our data indicate elevated risks in census tracts with inadequate infrastructure characterized by a higher proportion of households experiencing a lack of basic sanitation with the presence of open sewage, inadequate waste management, and/or a lack of electricity. In addition, incidences of maternal ZIKV infections and microcephaly were also found to correlate with social determinants of health, with clusters found in communities with high proportions of households with low per capita income, of racially minoritized women, and/or of women with low literacy.
In line with the findings of this research, two previous studies carried out in Recife confirmed a strong correlation between the distribution of maternal ZIKV infections [26] and microcephaly cases with poverty [27]. Notably, our results contrast the findings of a study carried out in the state of Rio Grande do Norte, Brazil, in which the highest notification of cases due to ZIKV infection was found in municipalities with a higher level of income, such as the state capital, Natal; the authors suggested the increased notifications in these areas likely reflect increased knowledge regarding the disease, better public health infrastructure, and a greater access to health services [28].
Although registered rates of ZIKV infection and cases of ZIKV-related microcephaly currently remain low, new cases continue to be reported across the country of Brazil with low seasonal peaks during the dry season between May and October [15]. The present study highlights geographic regions of Recife with heightened risks for the emergence of a new epidemic of ZIKV. Our findings demonstrate that, even after the epidemic period, cases of ZIKV in pregnant persons and microcephaly were concentrated in census tracts with relatively higher socioeconomic vulnerability, reinforcing the need for research to inform the development of social protection and environmental policies to mitigate ZIKV-related risks within these communities. Specifically, public policies should aim to address social inequalities and be tailored to effectively support populations with low purchasing power and those facing barriers to accessing high-quality health and education services.
Moreover, the infrastructure deficits of the high-risk areas (e.g., open sewage and inadequate waste disposal) present a favorable environment for breeding of Aedes spp. Mosquitoes [29]. Accelerated, unplanned urbanization processes contribute to socio-spatial weaknesses and an ecological imbalance, facilitating the proliferation of the Aedes spp. mosquitoes, thereby expanding the geographic range of arbovirus infections linked to the urban environment [28]. This study highlights the need for more effective actions and planning for environmental and vector control policies to combat the proliferation of Aedes mosquitoes, particularly within these high-risk clusters experiencing weaknesses in basic infrastructure [30–32].
The strengths and limitations of this study warrant consideration. This study has leveraged spatial autocorrelation in order to analyze the census tracts most vulnerable to ZIKV infection among pregnant persons and to microcephaly cases. The analysis has revealed disparities in risks between census tracts and also highlighted the influence of neighboring census tracts. While the global incidence serves as a good population-level disease indicator, local Moran’s I spatial statistical correlation provides a more refined understanding of ZIKV infection and microcephaly, directly linking them to socioeconomic factors and social determinants measured at the census tract level. Another strength is that this study used census tracts, which allowed for a more precise spatial visualization of the areas where the highest levels of incidence were concentrated. The chief limitations of the study involved the potential underreporting of cases. However, the surveillance of ZIKV did not change overtime therefore we would not expect that underreporting contributed significantly to this decrease. In addition, if underreporting occurred it is not likely that it was differential in areas with different socioeconomic conditions as notification of gestational infection and microcephaly were made compulsory by the Ministry of Health and the Zika laboratory tests were only available in the public sector. Therefore, it could impact in the number of cases, but not the spatial association between infection and socioeconomic conditions. Notably, a high proportion of ZIKV infections will be asymptomatic [33] or present with only mild symptoms and may, therefore, never registered in the SINAN-Zika notification system. Among cases submitted to the registration system, a subset of cases may remain unconfirmed while they remain under investigation. The use of secondary data may also introduce inconsistencies regarding the quality of the data provided, such as the high frequency of missing data, particularly regarding maternal race/ethnicity and educational level. It should also be highlighted that in the post-epidemic period, there was the COVID-19 pandemic, which may have interfered with notifying cases of maternal ZIKV infection and microcephaly. It is possible that uncontrolled variables may have influenced spatial correlations. As we used secondary data from the official dataset (RESP, SINAN, SINASC), it was not possible to adjust to confounders as this information was not available. However, Recife has an area of only 218.84 Km2, the climate is the same for the whole area. The climate may have changed from the epidemic period to the pos epidemic period. It would influence the number of cases, but we would not expect that it would affect the spatial correlation between socioeconomic conditions and ZIKV infection. In relation to coinfection, primary data from some studies showed that women were coinfected so the other infection (Chikungunya, Dengue and TORCH) [5] would not affect the spatial distribution of ZIKV infection.
Preventing and combating a new ZIKV epidemic will be no simple task. Overall, our findings provide robust evidence that the risks of ZIKV infections in pregnancy and microcephaly in Recife were increased in census tracts with increased deprivation and lower socioeconomic positions. More broadly, our findings reinforce the importance of risk mapping to inform effective planning to prevent infectious disease epidemics. The spatial distribution of socioeconomic inequalities should be taken into account when organizing strategic public health interventions, such as vector control activities, targeting the provision of social assistance, improving sanitation, social protection policies and continuous epidemiological monitoring, prioritizing areas with higher vulnerability. In the future, we recommend the use of more sophisticated spatial statistics tools that take into account the interrelation between the explanatory variables and their correlation with ZIKV infection and microcephaly.
Supporting information
S1 Table. Supplementary table.
Total percentages of each socioeconomic variables according 2010 Demographic Census (IBGE). Recife, Pernambuco.
https://doi.org/10.1371/journal.pntd.0013240.s001
(DOCX)
References
- 1. Postler TS, Beer M, Blitvich BJ, Bukh J, de Lamballerie X, Drexler JF, et al. Renaming of the genus Flavivirus to Orthoflavivirus and extension of binomial species names within the family Flaviviridae. Arch Virol. 2023;168(9):224. pmid:37561168
- 2.
Simmonds P, Becher P, Collett M, Gould E, Heinz F, Meyers G, et al. Family Flaviviridae. In: King A, Adams M, Carstens E, Lefkowitz E. Virus Taxonomy: Ninth Report of the International Committee on Taxonomy of Viruses. Elsevier Academic Press. 2012. 1003–20.
- 3. Duarte G, Moron AF, Timerman A, Fernandes CE, Mariani Neto C, de Almeida Filho GL, et al. Zika Virus Infection in Pregnant Women and Microcephaly. Rev Bras Ginecol Obstet. 2017;39(5):235–48. pmid:28575919
- 4. Song B-H, Yun S-I, Woolley M, Lee Y-M. Zika virus: History, epidemiology, transmission, and clinical presentation. J Neuroimmunol. 2017;308:50–64. pmid:28285789
- 5. Ximenes RA de A, Miranda-Filho D de B, Montarroyos UR, Martelli CMT, de Araújo TVB, Brickley E, et al. Zika-related adverse outcomes in a cohort of pregnant women with rash in Pernambuco, Brazil. PLoS Negl Trop Dis. 2021;15(3):e0009216. pmid:33684110
- 6. de Alencar Ximenes RA, Miranda-Filho D de B, Brickley EB, Barreto de Araújo TV, Montarroyos UR, Abtibol-Bernardino MR, et al. Risk of adverse outcomes in offspring with RT-PCR confirmed prenatal Zika virus exposure: An individual participant data meta-analysis of 13 cohorts in the Zika Brazilian Cohorts Consortium. Lancet Reg Health Am. 2023;17:100395. pmid:36714276
- 7. de Brito CAA, de Brito CCM, Oliveira AC, Rocha M, Atanásio C, Asfora C, et al. Zika in Pernambuco: rewriting the first outbreak. Rev Soc Bras Med Trop. 2016;49(5):553–8. pmid:27812648
- 8. Campos GS, Bandeira AC, Sardi SI. Zika Virus Outbreak, Bahia, Brazil. Emerg Infect Dis. 2015;21(10):1885–6. pmid:26401719
- 9. Teixeira MG, Costa M da CN, de Oliveira WK, Nunes ML, Rodrigues LC. The Epidemic of Zika Virus-Related Microcephaly in Brazil: Detection, Control, Etiology, and Future Scenarios. Am J Public Health. 2016;106(4):601–5. pmid:26959259
- 10. Garbin CAS, Teruel GP, Saliba TA, Moimaz SAS, Garbin AJÍ. Knowledge and attitude of women with high-risk pregnancy about the Zika virus transmission. Cien Saude Colet. 2021;26(1):233–40. pmid:33533844
- 11. Torres A. Enfermedad por virus de Zika y sus complicaciones neurológicas. Pediátr Panamá. 2017;46(2):41–5.
- 12. De Carvalho NS, De Carvalho BF, Fugaça CA, Dóris B, Biscaia ES. Zika virus infection during pregnancy and microcephaly occurrence: a review of literature and Brazilian data. Braz J Infect Dis. 2016;20(3):282–9. pmid:27102780
- 13. de Araújo TVB, Rodrigues LC, de Alencar Ximenes RA, de Barros Miranda-Filho D, Montarroyos UR, de Melo APL, et al. Association between Zika virus infection and microcephaly in Brazil, January to May, 2016: preliminary report of a case-control study. Lancet Infect Dis. 2016;16(12):1356–63. pmid:27641777
- 14. Azevedo C da S, Freire IM, Moura LN de F. Reorganizações familiares no contexto do cuidado ao bebê com Síndrome Congênita do Zika Vírus. Interface (Botucatu). 2021;25.
- 15. Costa MP, Ramalho ÂMC, de Sousa CM. Cenários de epidemias das aboviroses e riscos à saúde no Semiárido do Nordeste: enfrentamentos e desafios. RSD. 2022;11(6):e15911628580.
- 16. Queiroz ER da S, Medronho R de A. Spatial analysis of the incidence of Dengue, Zika and Chikungunya and socioeconomic determinants in the city of Rio de Janeiro, Brazil. Epidemiol Infect. 2021;149:e188. pmid:34338179
- 17. Fuller TL, Calvet G, Genaro Estevam C, Rafael Angelo J, Abiodun GJ, Halai U-A, et al. Behavioral, climatic, and environmental risk factors for Zika and Chikungunya virus infections in Rio de Janeiro, Brazil, 2015-16. PLoS One. 2017;12(11):e0188002. pmid:29145452
- 18. de Freitas DA, Wakimoto MD, Dias S, Souza-Santos R. High-Risk Areas for Congenital Zika Syndrome in Rio de Janeiro: Spatial Cluster Detection. Trop Med Infect Dis. 2024;9(5):105. pmid:38787038
- 19. Rosado LEP, de Aquino EC, Brickley EB, França DD da S, Silva FPA, da Silva VL, et al. Socioeconomic disparities associated with symptomatic Zika virus infections in pregnancy and congenital microcephaly: A spatiotemporal analysis from Goiânia, Brazil (2016 to 2020). PLoS Negl Trop Dis. 2022;16(6):e0010457. pmid:35714146
- 20. Power GM, Vaughan AM, Qiao L, Sanchez Clemente N, Pescarini JM, Paixão ES, et al. Socioeconomic risk markers of arthropod-borne virus (arbovirus) infections: a systematic literature review and meta-analysis. BMJ Glob Health. 2022;7(4):e007735. pmid:35428678
- 21.
BRASIL. Microcefalia. Brasília: Ministério da Saúde (MS); 2020. https://www.gov.br/saude/pt-br/assuntos/saude-de-a-az/m/microcefalia-1/microcefalia
- 22. Instituto Brasileiro de Geografia e Estatística IBGE. n.d. [cited 2022 November 7. ]. https://cidades.ibge.gov.br/brasil/pe/recife/panorama
- 23. de Oliveira WK, de França GVA, Carmo EH, Duncan BB, de Souza Kuchenbecker R, Schmidt MI. Infection-related microcephaly after the 2015 and 2016 Zika virus outbreaks in Brazil: a surveillance-based analysis. Lancet. 2017;390(10097):861–70. pmid:28647172
- 24. BRASIL, Ministério da Saúde (MS), Fundação Oswaldo Cruz (Fiocruz). Introdução à estatística espacial para a saúde pública. 2007 [cited on October 17, 2021. ]. http://www.escoladesaude.pr.gov.br/arquivos/File/TEXTOS_CURSO_VIGILANCIA/capacitacao_e_atualizacao_em_geoprocessamento_em_saude_3.pdf
- 25. Assunção RM, Barreto SM, Guerra HL, Sakurai E. Maps of epidemiological rates: a Bayesian approach. Cad Saude Publica. 1998;14(4):713–23. pmid:9878904
- 26. Lobkowicz L, Power GM, De Souza WV, Montarroyos UR, Martelli CMT, de Araùjo TVB, et al. Neighbourhood-level income and Zika virus infection during pregnancy in Recife, Pernambuco, Brazil: an ecological perspective, 2015-2017. BMJ Glob Health. 2021;6(12):e006811. pmid:34857522
- 27. de Souza WV, de Albuquerque M de FPM, Vazquez E, Bezerra LCA, Mendes A da CG, Lyra TM, et al. Microcephaly epidemic related to the Zika virus and living conditions in Recife, Northeast Brazil. BMC Public Health. 2018;18(1):130. pmid:29329574
- 28. Cunha LS, Medeiros WR, Lima Junior FAV, Pereira SA. Relationship between social inequality indicators and the spatial distribution of Zika Virus cases. Cien Saude Colet. 2020;25(5):1839–50. pmid:32402031
- 29. Machado JP, de Oliveira RM, Souza-Santos R. Spatial analysis of dengue occurrence and living conditions in Nova Iguaçu, Rio de Janeiro State, Brazil. Cad Saude Publica. 2009;25(5):1025–34. pmid:19488487
- 30.
Garcia L. Epidemia do vírus Zika e microcefalia no Brasil: emergência, evolução e enfrentamento: texto para discussão. 1st ed. Brasília: Livraria Ipea. 2018.
- 31. Nunes J, Pimenta D. A epidemia de Zika e os limites da saúde global. Lua Nova. 2016;98:21–46.
- 32. Fontoura FC, Cardoso MVLML. Association between congenital malformation and neonatal and maternal variables in neonatal units of a Northeast Brazilian city. Texto contexto - enferm. 2014;23(4):907–14.
- 33. Haby MM, Pinart M, Elias V, Reveiz L. Prevalence of asymptomatic Zika virus infection: a systematic review. Bull World Health Organ. 2018;96(6):402-413D. pmid:29904223