COVID-19 vaccination coverage of school-aged children in Santiago, Chile, correlates with socioeconomic status: Longitudinal observational study

COVID-19 vaccination coverage of school-aged children in Santiago, Chile, correlates with socioeconomic status: Longitudinal observational study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article COVID-19 vaccination coverage of school-aged children in Santiago, Chile, correlates with socioeconomic status: Longitudinal observational study Enzo Guerrero-Araya, Cesar Ravello, Mario Rosemblatt, Tomas Perez-Acle This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4547811/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract The burden of COVID-19 was heterogeneous, indicating that the effects of this disease are synergistic with both other non-communicable diseases and socioeconomic status (SES), highlighting its syndemic character. While the appearance of vaccines moderated the pandemic effects, their coverage was heterogeneous too, both when comparing different countries, and when comparing different populations within countries. Of note, once again SES appears to be a correlated factor. We analyzed publicly available data detailing the percentage of school-aged, vaccinated children in different municipalities belonging to the Metropolitan Area (MA) of Santiago, Chile. Vaccination data was compiled per school type, either public, state-subsidized, or private, at three different dates during the COVID-19 pandemic to cover the dispersion of Delta , Omicron , and its subvariants BA.4 and BA.5. We computed the median vaccination ratio for each municipality and school type and calculated their Spearman’s rank correlation coefficient with each one of nine SES indices. The percentage of school-age children who received vaccinations against COVID-19 correlates with SES. This strong correlation is observed in public and state-subsidized schools, but not in private schools. Although inequity in vaccination coverage decreased over time, it remained higher among students enrolled either in public or state-subsidized schools compared to those of private schools. Although available data was insufficient to explore plausible causes behind lower vaccination coverage, it is likely that a combination of factors including the lack of proper information about the importance of vaccination, the lack of incentives for children’s vaccination, low trust in the government, and limited access to vaccines for lower-income people, may all have contributed. These findings raise the need to design better strategies to overcome shortcomings in vaccination campaigns to confront future pandemics. Trial Registration: The present work does not involve clinical trials. Health sciences/Health care/Public health/Epidemiology Health sciences/Health care/Health policy Vaccination COVID-19 Inequality Children vaccination Figures Figure 1 Figure 2 Figure 3 Introduction As of October 2022, the pandemic caused by the novel coronavirus, SARS-CoV-2 has caused more than 6 million deaths worldwide [ 1 ]. After more than three years since the detection of the first case in China [ 2 ], COVID-19 continues to pose challenges: from the impact of anti-vaxxers movements [ 3 , 4 ] to the appearance of new variants such as Delta and Omicron [ 5 ]. In an unprecedented biotechnological response, vaccine manufacturers developed, and National Regulatory Authorities approved in record time, several vaccines that were proven safe and effective in diminishing infection, hospital admissions, and deaths rates [ 6 – 8 ]. However, unequal access to vaccines creates enormous risks not only for the population of developing countries but also for the rest of the world. In fact, the Gamma, Delta, and Omicron variants of SARS-CoV-2, the etiological agent of COVID-19, emerged from high prevalence conditions in Brazil, India, and the African continent, respectively, spreading rapidly throughout the world [ 5 ]. Additionally, due to the influence of anti-vaxxer movements driven by the abundance of fake news, anti-science, and the promotion of highly individualistic behaviors, assessing and comprehending the willingness to receive COVID-19 vaccination is essential for the development of more effective public policies aimed at promoting vaccination [ 9 – 11 ], while keeping a balance with strict restrictions and possible socioeconomic impact [ 12 ]. Over the course of three years, COVID-19 spread across the globe. However, its impact varied considerably depending on the socioeconomic status (SES) of the affected population. Several studies have reported associations between SES and COVID-19 incidence, mortality, and vaccination coverage [ 13 – 15 ]. Locally, a seminal study showed that during the first stages of the pandemic, mortality attributed to COVID-19 was higher in places with lower SES in the Metropolitan Area of Santiago, Chile [ 13 ]. Data exhibited by this study corroborated that COVID-19 is, in fact, a syndemic disease: an epidemiological condition whose burden among the population is synergistic with both non-communicable diseases and SES [ 16 , 17 ]. Thus, wealthier municipalities—usually more affluent and therefore healthier—were found to be less vulnerable to COVID-19. A similar correlation has been reported for other countries [ 18 ]. For instance, in the USA, localities with lower levels of education and a higher proportion of African American population–both factors usually associated but not equivalent to lower SES–are linked with a higher number of COVID-19 cases and fatalities, together with a higher proportion of long-term consequences of the infection [ 19 – 21 ]. Similarly, in Sweden, a higher number of COVID-19-related deaths, occurred in areas of lower SES [ 22 ], while in India, population density and literacy have been found to be positively and negatively correlated with COVID-19 infection rates, respectively, highlighting the syndemic nature of this disease [ 23 ]. In addition to the correlation between socioeconomic status (SES) and both the incidence and severity of COVID-19, vaccination rates have also been linked to SES at the country level. For example, some countries, such as Israel and Chile, accessed vaccines early in 2021, achieving coverage rates exceeding 90% of their populations [ 24 , 25 ]. In contrast, less affluent nations like Haiti have struggled to vaccinate even 5% of their population [ 23 , 26 ]. Thus, a lower proportion of the population receiving the COVID-19 vaccine has been associated with lower SES, a situation compounded by factors including unchecked immigration, political instability, and diminished trust in government [ 9 – 11 , 14 , 27 ]. Irregular immigrants often face limited access to healthcare services and typically reside in lower-income areas. Moreover, regions experiencing political unrest or where public trust in the government is low have difficulties in executing effective vaccination campaigns and, to an even greater extent, in persuading the population to adhere to mandates and guidelines. In addition to its successful COVID-19 vaccination campaign aimed at the general population [ 28 ], the Chilean government conducted an extensive vaccination program for children. By October 2022, over 90% of children aged 6 to 17 were fully vaccinated, having received at least two doses of the vaccine [ 29 ]. Following the government's authorization of COVID-19 vaccines for very young children, the Ministry of Education developed a 'safe back-to-school plan.' This plan included the lifting of seating capacity limitations in classrooms where vaccination rates exceeded 80% [ 30 ]. Notably, even before the completion of the vaccination campaign for children under 12 years old was achieved, class attendance restrictions were lifted, eroding the availability of incentives for children to be vaccinated. In contrast, all individuals above 12 years old were compelled by the Ministry of Health’s to have a Sanitary Pass certifying that the person was up to date with the vaccination timetable before attending cultural, shopping, and eating venues [ 31 ]. Although the level of vaccination for each school was closely monitored by the Chilean government, to the best of our knowledge, the relationship between SES, vaccination coverage and the nature of the school, was not assessed. In this study, we determined the SES of the 32 municipalities located in the Metropolitan Area of Santiago, the capital of Chile [ 32 ]. For each municipality we computed the median school vaccination coverage per school type, at three different dates distributed along the pandemic so to cover the spread of SARS-CoV-2 variants Delta and Omicron BA.4 and BA.5: November 15, 2021; March 1st, 2022; and May 26, 2022, respectively. Results Our results indicate a strong correlation between SES indices and the median school vaccination coverage. We further explored differences between school types, evaluating private, subsidized, and public schools' data separately. As expected, vulnerable municipalities with low SES exhibit lower levels of vaccination coverage. Surprisingly, while a strong correlation between vaccination coverage and SES is present in both public and state-subsidized schools, the correlation is meaningless for private schools. Therefore, in the latter, vaccination coverage seems to be independent of the SES of the municipality. Exploring the correlation between SES indices: all indices are correlated with SPI. Since the SPI index is only available for the city of Santiago, we evaluated the correlation between other SES indices and the SPI to determine whether other SES indices may be used as proxies to access the socioeconomic status of all municipalities in the Metropolitan Area of Santiago, Chile. Our results indicate that all the evaluated SES indices do correlate with SPI (Supplementary Fig. 1), with CDI being the one with the highest correlation strength (| ρ | > = 0.90) Vaccination coverage is correlated with SES in schools belonging to Santiago, Chile. In this study we evaluated the vaccination and SES data of students enrolled in the 1,667 schools belonging to the 34 municipalities of the Metropolitan Area of Santiago, Chile. We divided the population according to the school type: public, state-subsidized, and private schools. Their enrollments as of March 2021 were: 297,928 (29%), 575,426 (55%), 169,898 (16%), respectively. The population estimate of Santiago is 6,075,403 (30.9% of the country’s population). As in any other large city around the world, SES indices vary widely. For instance, the municipality of Providencia (Fig. 1 A; CDI rank 1) has the lowest rate of Multidimensional Poverty (0.034), whilst Lo Espejo (Fig. 1 A; CDI rank 33), has the highest rate of Multidimensional Poverty (0.375): more than 10 times higher than that of Providencia. As expected, the three municipalities with the highest CDI are also the ones with the highest level of vaccination coverage in schools (Table 1 and Fig. 1 A). In contrast, the four municipalities with the lowest CDI are those with the lowest vaccination coverage, except for Pedro Aguirre Cerda, a municipality exhibiting lower vaccination coverage and ranking 26th in CDI (Table 1 and Fig. 1 A). Notably, our study also shows that there are no municipalities with either high or medium vaccination coverage and low CDI could be found. Consequently, no municipalities with low vaccination coverage and high CDI can be identified (Table 1 and Fig. 1 A). Table 1 SES indices and vaccination coverage for each municipality. Ranking Municipality Vaccine % CDI Poverty Multidimensional poverty PHLBS Health and social welfare Economy and resources Education SVI SPI 1 Providencia 91,0 0,876 0,004 0,034 0,026 0,985 0,776 0,878 0,693 0,266 2 Las Condes 92,0 0,875 0,002 0,042 0,013 0,993 0,780 0,866 0,702 0,117 3 Santiago 89,0 0,778 0,041 0,096 0,173 0,895 0,635 0,828 0,738 0,571 4 Vitacura 91,0 0,764 0,001 0,035 0,005 0,995 0,498 0,900 0,588 0,063 5 Lo Barnechea 90,0 0,677 0,028 0,172 0,068 0,945 0,403 0,816 0,863 0,320 6 Ñuñoa 90,0 0,660 0,009 0,058 0,055 0,968 0,360 0,825 0,748 0,374 7 San Miguel 88,0 0,608 0,049 0,173 0,057 0,945 0,306 0,777 0,740 0,533 8 La Reina 89,0 0,607 0,010 0,069 0,051 0,970 0,282 0,819 0,756 0,325 9 Maipú 87,0 0,597 0,026 0,132 0,027 0,970 0,282 0,779 0,766 0,584 10 La Florida 86,0 0,589 0,045 0,190 0,037 0,954 0,284 0,755 0,766 0,593 11 Quilicura 86,0 0,577 0,057 0,179 0,025 0,949 0,267 0,757 0,787 0,560 12 Huechuraba 88,5 0,563 0,056 0,288 0,076 0,929 0,267 0,720 0,904 0,581 13 Pudahuel 84,0 0,552 0,083 0,225 0,075 0,909 0,250 0,740 0,857 0,651 14 La Cisterna 85,0 0,551 0,066 0,178 0,188 0,878 0,244 0,780 0,804 0,669 15 Macul 86,0 0,545 0,075 0,135 0,070 0,925 0,237 0,737 0,753 0,550 16 Independencia 86,0 0,540 0,085 0,209 0,056 0,915 0,231 0,747 0,752 0,714 17 Puente Alto 85,0 0,539 0,073 0,233 0,019 0,946 0,218 0,759 0,825 0,643 18 Recoleta 85,0 0,538 0,069 0,225 0,123 0,902 0,231 0,746 0,805 0,738 19 Quinta Normal 84,0 0,538 0,037 0,235 0,092 0,938 0,246 0,673 0,795 0,702 20 Peñalolén 87,0 0,530 0,044 0,263 0,089 0,930 0,216 0,742 0,872 0,641 21 Estación Central 84,0 0,530 0,058 0,235 0,139 0,907 0,228 0,720 0,766 0,699 22 San Bernardo 85,0 0,520 0,094 0,261 0,055 0,914 0,213 0,723 0,855 0,751 23 Cerrillos 82,5 0,489 0,065 0,274 0,060 0,933 0,192 0,653 0,827 0,644 24 Renca 82,0 0,478 0,037 0,245 0,080 0,940 0,173 0,673 0,875 0,685 25 San Joaquín 81,0 0,472 0,052 0,211 0,122 0,915 0,185 0,620 0,815 0,752 26 Pedro Aguirre Cerda 78,0 0,469 0,062 0,268 0,101 0,921 0,175 0,639 0,869 0,695 27 Conchalí 82,0 0,466 0,074 0,294 0,085 0,917 0,173 0,639 0,812 0,771 28 El Bosque 84,0 0,454 0,096 0,227 0,052 0,916 0,141 0,723 0,878 0,746 29 San Ramón 81,0 0,439 0,046 0,279 0,078 0,935 0,139 0,651 0,880 0,803 30 La Granja 83,0 0,427 0,048 0,219 0,080 0,936 0,128 0,646 0,896 0,701 31 Lo Prado 80,5 0,406 0,058 0,245 0,124 0,910 0,118 0,623 0,844 0,755 32 Lo Espejo 73,5 0,391 0,067 0,375 0,096 0,917 0,109 0,600 0,908 0,818 33 Cerro Navia 78,0 0,373 0,076 0,346 0,127 0,900 0,094 0,614 0,895 0,810 34 La Pintana 78,0 0,360 0,141 0,327 0,048 0,892 0,084 0,623 0,934 0,830 When analyzing the data gathered on May 26, 2022, three months after the peak of the Omicron spreading (around February 14), the correlation between each SES index and the median school vaccination for each municipality ranged from a very strong correlation, with a | ρ | > = 0.90 for the case of Economy and Resources, Education, CDI, and SPI indices; to a strong correlation, with a | ρ | > = 0.70 for the case of Multidimensional Poverty, and SVI; and to a moderate correlation, with | ρ | > 0.40 for the case of Poverty, PHLBS and Health and Social Welfare. All correlations were statistically significant ( p < 0.01) (Fig. 1 B). Of note, similar trends with different correlation values between SES indices and vaccination coverage were found on November 15, 2021, three days after the peak of the Delta variant spreading, and on March 5, 2022, in the middle of the second wave of Omicron infection produced by the dispersion of the BA.4/BA.5 subvariant (Supplementary Figs. 2 and 3). We further explored whether the correlation between the vulnerability of different municipalities and the vaccination coverage may be accounted for in the three main types of schools existing in Chile: private, state-subsidized, and public schools. While parents and tutors enrolling their school-aged children in private schools must pay a full tuition fee, in the case of state-subsidized schools, the tuition fee is importantly reduced by the state subsidy. In the case of public schools, the state covers the full tuition fee. Our analysis reveals that a similar correlation, as previously mentioned, exists within both state-subsidized and public schools, albeit with variations in the correlation values (Fig. 2 A-D). Unexpectedly, our analysis reveals no observable correlation between the vulnerability of municipalities and vaccination coverage within the population attending private schools. (Fig. 2 E-F). Progression of inequity in school vaccination coverage over time. With the aim to assess the inequity of the vaccination coverage, we calculated the p90/p40 ratio in three dates, covering the spread of different SARS-CoV-2 variants. We found that overall, inequity decreases in all school types over time along the COVID-19 pandemic (Fig. 3 ). Importantly, the largest reduction in the inequity of the COVID-19 vaccination coverage occurs between November 15, 2021, and March 01, 2022, after the peak of the Omicron variant dispersion. In all time periods analyzed, inequity in vaccination coverage persists at higher levels in public schools compared to private and state-subsidized schools. This occurs despite the existence of a significant correlation between the vulnerability of municipalities and vaccination coverage, indicating that lower SES is associated with reduced vaccination rates. Notably, this disparity in vaccination coverage is more pronounced in public schools. In contrast, both private and state-subsidized schools demonstrate greater equity in vaccination coverage, regardless of the SES of the municipality in which they are situated. Discussion This study revealed a correlation between 9 SES indices and the COVID-19 vaccination coverage in schools belonging to 34 municipalities of the Metropolitan Area of Santiago, Chile; one of the countries with the highest rate of vaccination in the world [ 28 ]. After analyzing the Spearman’s rank correlation between socioeconomic indices and COVID-19 vaccination coverage, we found a statistically significant correlation between lower SES and lower vaccination coverage. Even though inequity in vaccination coverage diminished over time along the pandemic, this inequity remains higher in public schools compared to that of private and state-subsidized schools, for all municipalities (Fig. 3 ). In general terms, our results are consistent with previous literature, indicating that vaccine coverage is lower in vulnerable populations living in poverty, having lower literacy and with a lesser educational level [ 14 , 27 , 33 ]. A potential rationale for these observations may be rooted in the varied personal beliefs across different SES groups. Specifically, one study noted a discernible negative correlation between SES and skepticism towards the COVID-19 vaccine’s secondary effects and conspiracy theories, offering an insightful perspective into our findings [ 34 ]. In addition to the statistically significant correlation between the vulnerability of different municipalities and the COVID-19 vaccination coverage–i.e. municipalities with lower SES exhibit lower coverage–, different school types exhibit distinct vaccination coverage. Thus, both public and state-subsidized schools show lower vaccination coverage than that of private schools. Although the strength of these correlations varies depending on the municipality (Fig. 2 ), this trend is maintained along the pandemic (Fig. 3 ). However, an important difference in vaccination coverage between school types, remains. Furthermore, analysis of vaccination coverage, in terms of percentages as reported by the Chilean government, uncovers significant differences across school types. However, a more alarming situation emerges when examining the raw numbers of unvaccinated children, particularly those attending schools with the lowest vaccination rates. The total number of children enrolled in public and state-subsidized schools, which demonstrate significantly lower vaccination coverage, is more than five times greater than that in private schools, with the respective figures being 873,354 and 169,898. This discrepancy highlights the critical issue of lower vaccination rates primarily among students in public and state-subsidized schools. Collectively, these two sectors account for approximately 84% of all student enrollments in the Metropolitan Area of Santiago, Chile. Considering that municipalities with lower SES are the ones having the highest population density [ 35 ], a lower vaccination coverage together with higher population density, are both key factors to consider when dealing with the higher burden of COVID-19 on these populations. Although the disparity in vaccination coverage diminishes over time, research has demonstrated that delays in vaccination schedules are associated with heightened adverse effects [ 36 ]. Available literature points to a combination of factors that may produce this uneven vaccination coverage. Among others, the lack of proper information about the importance and safety of vaccination, insufficient incentives for vaccination, religious beliefs, the negative view of pharmaceutical companies, and low trust in the government, may all have played a role in this uneven vaccination rate [ 9 – 11 , 14 , 27 , 37 ]. Research indicates that the impact of incentives on vaccination uptake varies across populations. Notably, monetary incentives have been found to be more effective than either encouraging messages or the promise of increased freedoms [ 38 , 39 ]. A critical consideration is that children typically do not independently decide to receive vaccinations; instead, these decisions are made by their parents or caregivers. A key factor influencing vaccination decisions is the perceived risk associated with the vaccine [ 36 ]. Although the correlations discussed herein do not show significance when considering the adult population, it is plausible that concerns regarding vaccine risk may be amplified in the context of vaccinating children. Specifically, adults might be willing to accept the perceived risk of vaccination for themselves but hesitate to subject their children to the same perceived risks. Beyond the willingness to vaccinate, logistical barriers play a crucial role in determining vaccination uptake differences. These include the availability of vaccine doses and the accessibility of vaccination centers, which is influenced by their location, transportation options, queue lengths, and operating hours. Such factors are particularly relevant for children, who require accompaniment by an adult to vaccination sites. This necessity poses additional challenges for households where both parents work and lack childcare support, potentially impacting vaccination rates. To enhance vaccination campaigns and public policies, a more intricate examination of these contributing factors is necessary. The reliance on broad data may risk simplifying the complexities of pandemics, underlining the importance of detailed, granular data in formulating responses to not only COVID-19 but future public health crises as well. One of the limitations of our study is that the SES indices correspond to the municipal averages, so we cannot perform analyses nor extract conclusions at a granular level. In other words, assuming that an averaging SES index of the municipality would be an adequate descriptor for the whole spectrum of wealth exhibited on the municipality could be considered as a naive approach. This limitation becomes evident when trying to explain the differences in vaccination coverage between school types; we can only assume that the sub-populations that are enrolled in private schools (16%) are those that can afford the high tuition costs corresponding to the least vulnerable families in each municipality. Conversely, students enrolled in state-subsidized or in public schools are considered most vulnerable to the burden of COVID-19 (84%). Anyhow, without further socioeconomic details at an individual student level, we can only speculate about the causal roots of this inequity in vaccination coverage. Considering that COVID-19 vaccination in Chile is free of charge and governmentally orchestrated, determining the causal roots behind the lower vaccination levels noted here is crucial to develop better public policies. For example, survey studies should include questions about willingness to vaccinate children and elderly dependents of the respondent and detailed socioeconomic and educational background, vaccination throughput of each vaccination center should be analyzed in detail and correlation analysis should be performed with more detailed, granular data. Even though we are unable to identify the causes of lower vaccination ratios among school-aged children in municipalities of lower, it is imperative that public policies counteract this behavior. Otherwise, the inequity in vaccination coverage will be perpetuated in future pandemics, exacerbating their impact on the more vulnerable population. Methods Data sources Socioeconomic status To generate a socioeconomic profile of the municipalities in Santiago, Chile, we used nine different SES indices so to obtain a broader multi-factorial socioeconomic description. It should be noted that the reliability of all indices referenced in this study is high, as they have been sourced directly from the Government of Chile or from previously published materials. While these indices represent the most current data publicly available, it is important to acknowledge the potential for changes in the socioeconomic indices subsequent to the time of data analysis. The Social Priority Index (SPI) was published in 2019 by the Regional Ministerial Secretariat of Social Development and Family. It is a synthetic index that integrates relevant aspects of communal social development, including income, education, and health [ 40 ]. The School Vulnerability Index (SVI) , published in 2021 by the National Board of School Aid and Scholarships (JUNAEB), is the ratio of the sum of the students in the first, second, and third priority ranking compared to the total school enrollment. Students are classified in priorities 1, 2, and 3 according to poverty conditions and risk of school failure. Thus, students living in lower socioeconomic conditions (Priority 1) tend to exhibit a higher risk of school failure, and thus receive the highest priority from the Board [ 41 ]. The Community Development Index (CDI) , published in 2020, is a comprehensive index that integrates three socioeconomic dimensions: Health and Social Welfare; Economy and Resources; and Education. The development of the CDI involves a meticulous process of selecting a variety of standardized and comparable indicators, aims to provide a reliable instrument for monitoring and quantifying the impact of development processes from a territorial perspective. The CDI, as well as its individual dimensions, is available for each municipality in the country [ 42 ], offering a tool for local management and decision-making. In this work, we have chosen to consider the CDI and its individual components separately. This decision stems from our aim to leverage the distinct yet complementary insights that the aggregate index and its underlying dimensions offer. The CDI provides a holistic view of community development across municipalities, facilitating broad comparisons and trend analysis. At the same time, analyzing the individual dimensions enables a deeper dive into specific areas of socioeconomic development, allowing for a nuanced understanding of strengths and challenges within each municipality. This dual approach enriches our analysis, contributing to a more comprehensive socioeconomic profile that can better inform targeted strategies for community development. The following indices are calculated as the percentage of people belonging to each category respectively for each municipality. Poverty is determined by a threshold defined as a function of income level and household size. Multidimensional Poverty is defined as being part of a household that cannot achieve adequate living conditions in a set of five relevant dimensions of well-being: (1) Education; (2) Health; (3) Labor and Social Security; (4) Housing and Environment; and (5) Networks and Social Cohesion. These conditions are measured through a weighted set of 15 indicators (three for each dimension). Households that accumulate deficiencies of 22.5% or more are classified as being in a situation of multidimensional poverty. The Poverty and Multidimensional Poverty indices were extracted from the National Socioeconomic Characterization Survey (CASEN) 2017, while the PHLBS , which is the percentage of People in Households Lacking Basic Services, was extracted from the Social Registry of Households 2020. Both instruments are used by the Ministry of Social Development to focus on social assistance among the population. [ 43 ]. The decision to evaluate these SES indices individually, rather than consolidating them into a single composite SES index, was driven by two primary considerations. First, analyzing the indices separately facilitates a nuanced understanding of the various dimensions of SES and their distinct impacts on vaccination coverage among school-aged children. Second, due to the complex and multifaceted nature of SES, a composite index could potentially obscure significant disparities and trends that are only discernible when these dimensions are examined on their own. This methodological approach aligns with our primary objective: to investigate the relationship between different aspects of SES and vaccination coverage in children, ensuring a more accurate and comprehensive analysis. Pandemic Data Data about new cases, deaths and other aspects was published regularly by the Ministry of Science, Technology and Innovation on their freely available repository [ 44 ]. Specifically, we used the Daily Total National Cases to visualize the changing trends following the arrival of the different variants and sub-variants. Vaccinations Even though in Chile the COVID-19 vaccination campaign is orchestrated and conducted by the Ministry of Health, the Ministry of Education publishes vaccination coverage per grade and school on its website [ 29 ]. To accurately assess the extent of vaccine coverage in each school and grade, the Ministry of Education combines its own database of school enrollments with the vaccination records from the Ministry of Health. This integration is accomplished by using the national identity number (RUT) of each student, which is the unique personal identifier in Chile. By using the RUT, they can precisely link each student’s school records with their vaccination status, ensuring a detailed and accurate understanding of the vaccination coverage across different educational institutions. To study whether the spread of different SARS-CoV-2 variants among the population might influence the vaccination process among school-age students in different municipalities in Santiago, Chile, we downloaded data published on November 15, 2021; March 1st, 2022; and May 26, 2022. By selecting these dates, we covered the spread of different SARS-CoV-2 variants: Delta in November, Omicron in March and Omicron subvariants BA.4-BA.5 in May [ 44 ]. The data shows the proportion of students in each school and grade who are fully vaccinated, partially vaccinated, or not vaccinated at all. ‘Fully vaccinated’ refers to students who have received all required doses of the COVID-19 vaccine, ‘partially vaccinated’ indicates those who have only received some but not all of the necessary doses, and ‘not vaccinated’ denotes students who have not received any doses of the vaccine. School metadata The Chilean Ministry of Education provides easily accessible metadata for each educational institution on their public repository [ 45 ]. This metadata was used to identify public, state-subsidized and private schools in every municipality. Statistical Analysis All statistical analyses were performed on the downloaded data by programming in Python v3.1 using the SciPy v1.7.1 package [ 46 ]. To measure inequity, we employed the percentile ratio p90/p40, inspired by The Palma ratio [ 47 ]. In this context, "p90" refers to the 90th percentile, representing the mean vaccination coverage among the top 10% of municipalities with the highest vaccination rates. Conversely, "p40" denotes the 40th percentile, representing the mean vaccination coverage among the bottom 40% of municipalities with the lowest vaccination rates. To compute the ratio, we divided the mean vaccination coverage of the municipalities at the 90th percentile by the mean vaccination coverage of municipalities at the 40th percentile. The essence of using the p90/p40 ratio is that it highlights disparities in vaccination coverage, with maximum equity being indicated when the ratio equals 1. The calculation of the mean vaccination coverage for the highest 10% of municipalities (p90) involves aggregating the vaccination rates of municipalities that fall into the 90th percentile and then calculating the average. This figure represents the benchmark for high vaccination coverage within the sample and enables a comparison with lower-performing municipalities to assess equity in vaccination distribution. Spearman’s rank-order correlation was computed using Statsmodels v0.13.1. Plots were made with Seaborn v0.11.2. Ethical considerations All data used in this research was sourced in an anonymous form. Abbreviations CDI Community development index MA Metropolitan area PHLBS People in households lacking basic services SES Socioeconomic status SPI Social priority index SVI School vulnerability index Declarations Funding This material is based upon work supported by the U.S. Air Force Office of Scientific Research under award number FA9550-20-1-0196. Financial support is also acknowledged to Centro Ciencia & Vida, FB210008, Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia de ANID. Funding sources had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. AI use Disclosure Generative AI tools (ChatGPT using GPT-4) were used only to check style and grammar in some paragraphs. Data Availability The whole dataset as well as the python code used to perform the statistical analyses presented here are available on GitHub in the following repository. https://github.com/DLab/SantiagoSchoolVax Conflicts of Interest None declared. Abbreviations CDI: Community development index MA: Metropolitan area PHLBS: People in households lacking basic services. SES: Socioeconomic status SPI: Social priority index SVI: School vulnerability index Author contributions Enzo Guerrero-Araya: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Visualization, Writing. Cesar Ravello: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing. Mario Rosemblatt: Resources, Supervision, Project Administration, Writing Tomás Pérez-Acle: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing. Enzo Guerrero-Araya and Cesar Ravello share the first authorship. References Ritchie, H. et al. Coronavirus (COVID-19) Deaths Web Page. 2022. https://ourworldindata.org/covid-deaths . WHO. Listings of WHO’s response to COVID-19 Web Page. 2022. https://www.who.int/news/item/29-06-2020-covidtimeline . Burgess, R. A. et al. The COVID-19 vaccines rush: participatory community engagement matters more than ever. Lancet 397, 8–10. issn: 1474-547X 0140–6736. (2021). PMID: 33308484 Burki, T. The online anti-vaccine movement in the age of COVID-19. The Lancet Digital Health 2, e504–e505 (2020). PMID: 32984795 Aleem, A., Akbar Samad, A. B. & Slenker, A. K. Emerging Variants of SARS-CoV-2 And Novel Therapeutics Against Coronavirus (COVID-19) in StatPearls (StatPearls Publishing, 2022). PMID: 34033342 Baden, L. R. et al. Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine. N Engl J Med 384, 403–416. issn: 1533–4406 0028-4793. (2021). PMID: 33378609 Polack, F. P. et al. Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine. N Engl J Med 383. issn: 1533–4406 0028-4793. (2020). PMID: 33301246 Jara, A. et al. Effectiveness of an Inactivated SARS-CoV-2 Vaccine in Chile. N Engl J Med 385, 875–884. issn: 1533–4406 0028-4793. (2021). PMID: 34233097 Weitzer, J. et al. Willingness to receive an annual COVID-19 booster vaccine in the Germanspeaking DA-CH region in Europe: A cross-sectional study. The Lancet Regional Health-Europe 18, 100414 (2022). PMID: 35651957 De Giorgio, A. et al. Willingness to Receive COVID-19 Booster Vaccine: Associations between Green-Pass, Social Media Information, Anti-Vax Beliefs, and Emotional Balance. Vaccines 10. issn: 2076-393X. https://www.mdpi.com /2076-393X/10/3/481 (2022). PMID: 35335113 Lee, S. K., Sun, J., Jang, S. & Connelly, S. Misinformation of COVID-19 vaccines and vaccine hesitancy. Scientific reports 12, 1–11 (2022). PMID: 35953500 Coccia M. Improving preparedness for next pandemics: Max level of COVID-19 vaccinations without social impositions to design effective health policy and avoid flawed democracies. Environ Res. 2022;213:113566. doi: 10.1016/j.envres.2022.113566 . Epub 2022 May 31. PMID: 35660409; PMCID: PMC9155186. Mena, G. E. et al. Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile. Science 372. issn: 1095–9203 0036-8075. (2021). PMID: 33906968 Caspi, G. et al. Socioeconomic disparities and COVID-19 vaccination acceptance: a nationwide ecologic study. Clin Microbiol Infect 27, 1502–1506. issn: 1469 – 0691 1198-743X. (2021). PMID: 34111591 Saban, M., Myers, V., Ben-Shetrit, S. & Wilf-Miron, R. Socioeconomic gradient in COVID-19 vaccination: evidence from Israel. Int J Equity Health 20, 242. issn: 1475–9276 14759276. (2021). PMID: 34749718 Horton, R. Offline: COVID-19 is not a pandemic. The lancet 396, 874 (2020). PMID: 32979964 Vineis, P. COVID-19 as a syndemic: from inequalities to biological embodiment. European Journal of Public Health 31, 164–004 (2021). PMCID: PMC8574607 Wachtler, B. et al. Socioeconomic inequalities and COVID-19 - A review of the current international literature. J Health Monit 5, 3–17. issn: 2511–2708 2511–2708. (2020). PMID: 35146298 Hawkins, R. B., Charles, E. J. & Mehaffey, J. H. Socio-economic status and COVID-19-related cases and fatalities. Public Health 189, 129–134. issn: 1476–5616 0033-3506. (2020). PMID: 33227595 Gaglioti, A. H. et al. Population-Level Disparities in COVID-19: Measuring the Independent Association of the Proportion of Black Population on COVID-19 Cases and Deaths in US Counties. J Public Health Manag Pract 27, 268–277. issn: 1550–5022 1078–4659. (2021). PMID: 33762542 Berger, Z., Altiery, D. E. J. V., Assoumou, S. A. & Greenhalgh, T. Long COVID and Health Inequities: The Role of Primary Care. Milbank Q 99, 519–541. issn: 1468-0009 0887378X. (2021). PMID: 33783907 Strang, P., Furst, P. & Schultz, T. Excess deaths from COVID-19 correlate with age and socioeconomic status. A database study in the Stockholm region. Ups J Med Sci 125, 297–304. (2020). PMID: 33100083 Tamrakar, V. et al. District level correlates of COVID-19 pandemic in India during March-October 2020. PLoS One 16, e0257533. issn: 1932–6203 1932–6203. (2021). PMID: 34591892 Mathieu, E. et al. A global database of COVID-19 vaccinations. Nat Hum Behav 5, 947–953.issn: 2397–3374 2397–3374. (2021). PMID: 33972767 Balicer, R. D. & Ohana, R. Israel’s COVID-19 endgame 2021. WHO COVID-19 Dashboard. Geneva: World Health Organization, 2020. https://covid19.who.int/region/amro/country/ht . Débarre, F., Lecoeur, E., Guimier, L., Jauffret-Roustide, M. & Jannot, A.-S. The French Covid-19 vaccination policy did not solve vaccination inequities: a nationwide study on 64.5 million people. The European Journal of Public Health 32, 825–830. issn: 1101–1262 (2022). PMID: 36102834 Castillo, C., Dintrans, P. V. & Maddaleno, M. The successful COVID-19 vaccine rollout in Chile: Factors and challenges. Vaccine X 9, 100114 (2021). PMID: 34518818 Ministerio de Educación, C. Avance de la vacunación contra el COVID-19 por colegio Web Page. Jan. 2022. https://vacunacionescolar.mineduc.cl/ . Ministerio de Educación, C. Imparte lineamientos generales para la Planificacion del año escolar 2022 Online Document. 2021. https://www.mineduc.cl/wp-content/uploads/sites/19/ 2021/11/LineamientosEscolar2022.pdf . Ministerio de Salud, C. Pase de Movilidad Online Document. 2022. https://www.chileatiende.gob.cl/fichas/107011/2/pdf . Banzhaf, E., Reyes-Paecke, S., Muller, A. & Kindler, A. Do demographic and land-use changes contrast urban and suburban dynamics? A sophisticated reflection on Santiago de Chile. Habitat International 39, 179–191. issn: 0197–3975. https://www.sciencedirect.com/science/article/pii/S0197397512000860 (2013). Ministerio de Ciencia Tecnología Conocimiento e Innovación, C. Totales Nacionales Diarios Online Database. 2021. https://github.com/MinCiencia/Datos-COVID19/tree/master/output/producto5 Schober, P., Boer, C. & Schwarte, L. A. Correlation Coefficients: Appropriate Use and Interpretation. Anesth Analg 126, 1763–1768. issn: 1526–7598 0003-2999. (2018). PMID: 29481436 Barry, V. et al. Patterns in COVID-19 Vaccination Coverage, by Social Vulnerability and Urbanicity - United States, December 14, 2020-May 1, 2021. MMWR Morb Mortal Wkly Rep 70. 1545-861x, 818–824 (2021). PMID: 34081685 Salazar-Fernández C, Baeza-Rivera MJ, Villanueva M, Bautista JAP, Navarro RM, Pino M. Predictors of COVID-19 Vaccine Intention: Evidence from Chile, Mexico, and Colombia. Vaccines. 2022; 10(7):1129. https://doi.org/10.3390/vaccines10071129 Livert Aquino, F. & Gainza, X. Understanding density in an uneven city, Santiago de Chile: implications for social and environmental sustainability. Sustainability 6, 5876–5897 (2014). Coccia, M., Optimal levels of vaccination to reduce COVID-19 infected individuals and deaths: A global analysis, Environmental Research, Volume 204, Part C, 2022, 112314, ISSN 0013-9351, https://doi.org/10.1016/j.envres.2021.112314 . Lazarus, J. V. et al. Revisiting COVID-19 vaccine hesitancy around the world using data from 23 countries in 2021. Nat Commun 13, 3801 (2022). PMID: 35778396 Mardi P, Djalalinia S, Kargar R, Jamee M, Esmaeili Abdar Z, Qorbani M. Impact of incentives on COVID-19 vaccination; A systematic review. Frontiers in medicine. 2022;9:810323. Klüver H, Hartmann F, Humphreys M, Geissler F, Giesecke J. Incentives can spur COVID-19 vaccination uptake. Proceedings of the National Academy of Sciences. 2021;118(36):e2109543118. Secretaría Regional Ministerial de Desarrollo Social y Familia, C. Indice De Prioridad Social De Comunas 2019 Online Document. 2019. http://www.desarrollosocialyfamilia.gob.cl/storage/docs/INDICE.%5C_DE%5C_PRIORIDAD%5C_SOCIAL%5C_2019.pdf%7D . JUNAEB. Indice de Vulnerabilidad Escolar Web Page. 2022. https://www.junaeb.cl/ive . Hernández Bonivento, J. et al. Indice de Desarrollo Comunal. Chile 2020. Aplica (2020). doi: https://doi.org/10.32457/ISBN9789568454944962020-ED1 Ministerio de Desarrollo Social y Familia, C. Encuesta Casen en Pandemia Web Page. 2020. http://observatorio.ministeriodesarrollosocial.gob.cl/encuesta-casen-en-pandemia 2020. Ministerio de Educación, C. Directorio de Establecimientos Educacionales Web Page. Jan. 2022. ttps://datosabiertos.mineduc.cl/directorio-de-%20establecimientos-educacionales/ . Virtanen, P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods 17, 261–272. issn: 1548–7105 1548–7091. (2020). PMID: 32015543 Palma, J. G. Homogeneous Middles vs. Heterogeneous Tails, and the End of the ‘Inverted-U’: It’s All About the Share of the Rich. Development and Change 42, 87–153. eprint: https://onlinelibrary.wiley.com/doi/pdf/ 10.1111/j.1467-7660.2011.01694.x . (2011). Additional Declarations No competing interests reported. Supplementary Files COVID19vaccinationcoverageofschoolagedchildreninSantiagoChilecorrelateswithSESSUPP.docx Cite Share Download PDF Status: Published Journal Publication published 09 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 18 Jul, 2024 Reviews received at journal 16 Jul, 2024 Reviews received at journal 03 Jul, 2024 Reviewers agreed at journal 01 Jul, 2024 Reviewers agreed at journal 24 Jun, 2024 Reviewers invited by journal 24 Jun, 2024 Editor assigned by journal 24 Jun, 2024 Editor invited by journal 10 Jun, 2024 Submission checks completed at journal 08 Jun, 2024 First submitted to journal 07 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4547811","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":317889563,"identity":"f6ad7aa9-f52b-4a2b-adb1-9ced23975e5d","order_by":0,"name":"Enzo Guerrero-Araya","email":"","orcid":"","institution":"Fundación Ciencia \u0026 Vida","correspondingAuthor":false,"prefix":"","firstName":"Enzo","middleName":"","lastName":"Guerrero-Araya","suffix":""},{"id":317889564,"identity":"c74ccda5-17df-4244-800d-39e104427052","order_by":1,"name":"Cesar Ravello","email":"","orcid":"","institution":"Fundación Ciencia \u0026 Vida","correspondingAuthor":false,"prefix":"","firstName":"Cesar","middleName":"","lastName":"Ravello","suffix":""},{"id":317889565,"identity":"a7a98406-8362-4a26-9689-348bf78eb030","order_by":2,"name":"Mario Rosemblatt","email":"","orcid":"","institution":"Fundación Ciencia \u0026 Vida","correspondingAuthor":false,"prefix":"","firstName":"Mario","middleName":"","lastName":"Rosemblatt","suffix":""},{"id":317889566,"identity":"fb8ba379-07fa-4d5d-b6ca-01f798361b0b","order_by":3,"name":"Tomas Perez-Acle","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIie2QMUsDMRSAnwRyS+ytDyzNX7gjg4voX8lx0OnEVbBg4eCmYteKCv4HwTklEJe6O3SoFG664YogHY5ibnHKFboJ5oPA4+V9770EwOP5y/SAKJA2oPYotqfy944ClQcrLHKkHVyc5Kaum3NOg8mmXl0veS9YxKoaweB0+uye0jfp/YylccHeX1AuShtk0fzRgOh/rNwKZoIwJJLi5SskhZYUhlIzCskMVYdy9UWa6FZSXpWQ7KwSllbZ7VMyQkDaSmw7j9sgVfq4sEo4ditLI44m6s0+YShQGh0XuFbzpzsUiO4fCx7yNWybGx4G+nOzHWnOp0leV99nAwzdi0FHqzaP8jDF0jXF4/F4/hs/OyxZyCg/5JMAAAAASUVORK5CYII=","orcid":"","institution":"Fundación Ciencia \u0026 Vida","correspondingAuthor":true,"prefix":"","firstName":"Tomas","middleName":"","lastName":"Perez-Acle","suffix":""}],"badges":[],"createdAt":"2024-06-07 19:12:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4547811/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4547811/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-84260-z","type":"published","date":"2025-01-09T15:57:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59292021,"identity":"0037bb9b-e010-43ee-abae-1d7d68289793","added_by":"auto","created_at":"2024-06-28 18:50:27","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":387200,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between school vaccination coverage and SES Indices in Santiago, Chile as of May 26, 2022. Panel A), municipalities are colored according to their school vaccination coverage and their Community Development Index (CDI) in a Bivariate Map. Municipalities are numbered according to their rank in CDI from higher to lower values. The color coding is shown adjacent to the map using a 3 by 3 matrix where the CDI increases from left to right and the vaccination coverage increases from bottom to top. The values are grouped into three levels. The number labeled in each municipality is sorted by decreasing ranking according to the CDI and can be seen in Table 1. (B) The correlation value between six SES Indices and the median school vaccination coverage was evaluated in the 34 municipalities of the Metropolitan Area of Santiago, Chile. \u003cem\u003eρ \u003c/em\u003e= Spearman’s rank correlation coefficient; p = p-value.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4547811/v1/f4cdb26154d0fe545055053e.jpeg"},{"id":59292020,"identity":"ed480464-7cba-4f6c-8388-a6504b580deb","added_by":"auto","created_at":"2024-06-28 18:50:27","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":649331,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between school vaccination coverage and SES Indices by school category in the Metropolitan Area of Santiago as of May 26, 2022. All maps represent Municipalities from the Metropolitan Area of Santiago. They appear colored according to their school vaccination coverage and their Community Development Index (CDI) in a Bivariate Map. Municipalities are numbered according to their rank in CDI from higher to lower values. The color coding is shown adjacent to the map using a 3 by 3 matrix, where the CDI increases from left to right and the vaccination coverage increases from bottom to top. The values are grouped into three levels. The number labeled in each municipality is sorted following a decreasing ranking according to the CDI, and can be seen in Table 1. Next to each map, the correlation of six SES indices and the median school vaccination coverage is show. \u003cem\u003eρ \u003c/em\u003e= Spearman’s rank correlation coefficient; p = p-value. (AB) Public schools' data. (CD) Private subsidized schools' data. (EF) Private schools' data.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4547811/v1/908da4d6ecbcd84b1e873f18.jpeg"},{"id":59292024,"identity":"83a44a22-b75a-4857-8060-d1b16e93a0e2","added_by":"auto","created_at":"2024-06-28 18:50:27","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":37987,"visible":true,"origin":"","legend":"\u003cp\u003eInequity assessment of COVID-19 vaccination coverage in Santiago, Chile. The p90/p40 ratio is used to evaluate the inequity of the vaccination coverage for each school type at three time points along the COVID-19 pandemic: on November 15, 2021; March 1st, 2022; and May 26, 2022, covering the spread of different SARS-CoV-2 variants: \u003cem\u003eDelta\u003c/em\u003e, \u003cem\u003eOmicron \u003c/em\u003eand \u003cem\u003eOmicron BA.4-BA.5\u003c/em\u003e, respectively. Error bars represent the variability in the p90/p40 ratio, estimated based on 1000 bootstrap samples. While inequity in vaccination coverage between schools’ type tend to diminish over time, it remains higher in public schools than that of the other types.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4547811/v1/8aadd0215baceda95b161ded.jpg"},{"id":73694784,"identity":"73231dfc-42bd-4773-b015-77fd572d521a","added_by":"auto","created_at":"2025-01-13 16:14:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2026656,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4547811/v1/331bfd09-38f2-4543-a887-b1970f9c3353.pdf"},{"id":59292022,"identity":"a13decc8-e7b5-4bba-a9e8-afc59904582b","added_by":"auto","created_at":"2024-06-28 18:50:27","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2299299,"visible":true,"origin":"","legend":"","description":"","filename":"COVID19vaccinationcoverageofschoolagedchildreninSantiagoChilecorrelateswithSESSUPP.docx","url":"https://assets-eu.researchsquare.com/files/rs-4547811/v1/a40228e7cf04f270662ebe3d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"COVID-19 vaccination coverage of school-aged children in Santiago, Chile, correlates with socioeconomic status: Longitudinal observational study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAs of October 2022, the pandemic caused by the novel coronavirus, SARS-CoV-2 has caused more than 6\u0026nbsp;million deaths worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. After more than three years since the detection of the first case in China [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], COVID-19 continues to pose challenges: from the impact of anti-vaxxers movements [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] to the appearance of new variants such as Delta and Omicron [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In an unprecedented biotechnological response, vaccine manufacturers developed, and National Regulatory Authorities approved in record time, several vaccines that were proven safe and effective in diminishing infection, hospital admissions, and deaths rates [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, unequal access to vaccines creates enormous risks not only for the population of developing countries but also for the rest of the world. In fact, the Gamma, Delta, and Omicron variants of SARS-CoV-2, the etiological agent of COVID-19, emerged from high prevalence conditions in Brazil, India, and the African continent, respectively, spreading rapidly throughout the world [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Additionally, due to the influence of anti-vaxxer movements driven by the abundance of fake news, anti-science, and the promotion of highly individualistic behaviors, assessing and comprehending the willingness to receive COVID-19 vaccination is essential for the development of more effective public policies aimed at promoting vaccination [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], while keeping a balance with strict restrictions and possible socioeconomic impact [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOver the course of three years, COVID-19 spread across the globe. However, its impact varied considerably depending on the socioeconomic status (SES) of the affected population. Several studies have reported associations between SES and COVID-19 incidence, mortality, and vaccination coverage [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Locally, a seminal study showed that during the first stages of the pandemic, mortality attributed to COVID-19 was higher in places with lower SES in the Metropolitan Area of Santiago, Chile [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Data exhibited by this study corroborated that COVID-19 is, in fact, a syndemic disease: an epidemiological condition whose burden among the population is synergistic with both non-communicable diseases and SES [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Thus, wealthier municipalities\u0026mdash;usually more affluent and therefore healthier\u0026mdash;were found to be less vulnerable to COVID-19. A similar correlation has been reported for other countries [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. For instance, in the USA, localities with lower levels of education and a higher proportion of African American population\u0026ndash;both factors usually associated but not equivalent to lower SES\u0026ndash;are linked with a higher number of COVID-19 cases and fatalities, together with a higher proportion of long-term consequences of the infection [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Similarly, in Sweden, a higher number of COVID-19-related deaths, occurred in areas of lower SES [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], while in India, population density and literacy have been found to be positively and negatively correlated with COVID-19 infection rates, respectively, highlighting the syndemic nature of this disease [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to the correlation between socioeconomic status (SES) and both the incidence and severity of COVID-19, vaccination rates have also been linked to SES at the country level. For example, some countries, such as Israel and Chile, accessed vaccines early in 2021, achieving coverage rates exceeding 90% of their populations [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In contrast, less affluent nations like Haiti have struggled to vaccinate even 5% of their population [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Thus, a lower proportion of the population receiving the COVID-19 vaccine has been associated with lower SES, a situation compounded by factors including unchecked immigration, political instability, and diminished trust in government [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Irregular immigrants often face limited access to healthcare services and typically reside in lower-income areas. Moreover, regions experiencing political unrest or where public trust in the government is low have difficulties in executing effective vaccination campaigns and, to an even greater extent, in persuading the population to adhere to mandates and guidelines.\u003c/p\u003e \u003cp\u003eIn addition to its successful COVID-19 vaccination campaign aimed at the general population [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], the Chilean government conducted an extensive vaccination program for children. By October 2022, over 90% of children aged 6 to 17 were fully vaccinated, having received at least two doses of the vaccine [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Following the government's authorization of COVID-19 vaccines for very young children, the Ministry of Education developed a 'safe back-to-school plan.' This plan included the lifting of seating capacity limitations in classrooms where vaccination rates exceeded 80% [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Notably, even before the completion of the vaccination campaign for children under 12 years old was achieved, class attendance restrictions were lifted, eroding the availability of incentives for children to be vaccinated. In contrast, all individuals above 12 years old were compelled by the Ministry of Health\u0026rsquo;s to have a Sanitary Pass certifying that the person was up to date with the vaccination timetable before attending cultural, shopping, and eating venues [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough the level of vaccination for each school was closely monitored by the Chilean government, to the best of our knowledge, the relationship between SES, vaccination coverage and the nature of the school, was not assessed. In this study, we determined the SES of the 32 municipalities located in the Metropolitan Area of Santiago, the capital of Chile [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. For each municipality we computed the median school vaccination coverage per school type, at three different dates distributed along the pandemic so to cover the spread of SARS-CoV-2 variants Delta and Omicron BA.4 and BA.5: November 15, 2021; March 1st, 2022; and May 26, 2022, respectively.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOur results indicate a strong correlation between SES indices and the median school vaccination coverage. We further explored differences between school types, evaluating private, subsidized, and public schools' data separately. As expected, vulnerable municipalities with low SES exhibit lower levels of vaccination coverage. Surprisingly, while a strong correlation between vaccination coverage and SES is present in both public and state-subsidized schools, the correlation is meaningless for private schools. Therefore, in the latter, vaccination coverage seems to be independent of the SES of the municipality.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExploring the correlation between SES indices: all indices are correlated with SPI.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSince the SPI index is only available for the city of Santiago, we evaluated the correlation between other SES indices and the SPI to determine whether other SES indices may be used as proxies to access the socioeconomic status of all municipalities in the Metropolitan Area of Santiago, Chile. Our results indicate that all the evaluated SES indices do correlate with SPI (Supplementary Fig.\u0026nbsp;1), with CDI being the one with the highest correlation strength (|\u003cem\u003eρ\u003c/em\u003e| \u003cem\u003e\u0026gt;\u003c/em\u003e= 0.90)\u003c/p\u003e \u003cp\u003e \u003cb\u003eVaccination coverage is correlated with SES in schools belonging to Santiago, Chile.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn this study we evaluated the vaccination and SES data of students enrolled in the 1,667 schools belonging to the 34 municipalities of the Metropolitan Area of Santiago, Chile. We divided the population according to the school type: public, state-subsidized, and private schools. Their enrollments as of March 2021 were: 297,928 (29%), 575,426 (55%), 169,898 (16%), respectively. The population estimate of Santiago is 6,075,403 (30.9% of the country\u0026rsquo;s population). As in any other large city around the world, SES indices vary widely. For instance, the municipality of Providencia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA; CDI rank 1) has the lowest rate of Multidimensional Poverty (0.034), whilst Lo Espejo (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA; CDI rank 33), has the highest rate of Multidimensional Poverty (0.375): more than 10 times higher than that of Providencia. As expected, the three municipalities with the highest CDI are also the ones with the highest level of vaccination coverage in schools (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). In contrast, the four municipalities with the lowest CDI are those with the lowest vaccination coverage, except for Pedro Aguirre Cerda, a municipality exhibiting lower vaccination coverage and ranking 26th in CDI (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Notably, our study also shows that there are no municipalities with either high or medium vaccination coverage and low CDI could be found. Consequently, no municipalities with low vaccination coverage and high CDI can be identified (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSES indices and vaccination coverage for each municipality.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRanking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMunicipality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVaccine %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePoverty\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultidimensional poverty\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePHLBS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHealth and social welfare\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEconomy and resources\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSVI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eSPI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProvidencia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLas Condes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSantiago\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,571\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVitacura\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLo Barnechea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026Ntilde;u\u0026ntilde;oa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSan Miguel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,533\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLa Reina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaip\u0026uacute;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLa Florida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,593\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuilicura\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,560\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuechuraba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,581\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePudahuel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLa Cisterna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,669\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMacul\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndependencia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePuente Alto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRecoleta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,738\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuinta Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePe\u0026ntilde;alol\u0026eacute;n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,641\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstaci\u0026oacute;n Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,699\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSan Bernardo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,751\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCerrillos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRenca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSan Joaqu\u0026iacute;n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,752\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePedro Aguirre Cerda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConchal\u0026iacute;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,771\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEl Bosque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,746\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSan Ram\u0026oacute;n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLa Granja\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,701\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLo Prado\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,755\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLo Espejo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,818\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCerro Navia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,810\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLa Pintana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0,084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0,623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0,934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0,830\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen analyzing the data gathered on May 26, 2022, three months after the peak of the \u003cem\u003eOmicron\u003c/em\u003e spreading (around February 14), the correlation between each SES index and the median school vaccination for each municipality ranged from a very strong correlation, with a |\u003cem\u003eρ\u003c/em\u003e| \u003cem\u003e\u0026gt;\u003c/em\u003e= 0.90 for the case of Economy and Resources, Education, CDI, and SPI indices; to a strong correlation, with a |\u003cem\u003eρ\u003c/em\u003e| \u003cem\u003e\u0026gt;\u003c/em\u003e= 0.70 for the case of Multidimensional Poverty, and SVI; and to a moderate correlation, with |\u003cem\u003eρ\u003c/em\u003e| \u003cem\u003e\u0026gt;\u003c/em\u003e 0.40 for the case of Poverty, PHLBS and Health and Social Welfare. All correlations were statistically significant (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Of note, similar trends with different correlation values between SES indices and vaccination coverage were found on November 15, 2021, three days after the peak of the \u003cem\u003eDelta\u003c/em\u003e variant spreading, and on March 5, 2022, in the middle of the second wave of \u003cem\u003eOmicron\u003c/em\u003e infection produced by the dispersion of the BA.4/BA.5 subvariant (Supplementary Figs.\u0026nbsp;2 and 3).\u003c/p\u003e \u003cp\u003eWe further explored whether the correlation between the vulnerability of different municipalities and the vaccination coverage may be accounted for in the three main types of schools existing in Chile: private, state-subsidized, and public schools. While parents and tutors enrolling their school-aged children in private schools must pay a full tuition fee, in the case of state-subsidized schools, the tuition fee is importantly reduced by the state subsidy. In the case of public schools, the state covers the full tuition fee. Our analysis reveals that a similar correlation, as previously mentioned, exists within both state-subsidized and public schools, albeit with variations in the correlation values (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-D). Unexpectedly, our analysis reveals no observable correlation between the vulnerability of municipalities and vaccination coverage within the population attending private schools. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE-F).\u003c/p\u003e \u003cp\u003e \u003cb\u003eProgression of inequity in school vaccination coverage over time.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWith the aim to assess the inequity of the vaccination coverage, we calculated the p90/p40 ratio in three dates, covering the spread of different SARS-CoV-2 variants. We found that overall, inequity decreases in all school types over time along the COVID-19 pandemic (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Importantly, the largest reduction in the inequity of the COVID-19 vaccination coverage occurs between November 15, 2021, and March 01, 2022, after the peak of the \u003cem\u003eOmicron\u003c/em\u003e variant dispersion. In all time periods analyzed, inequity in vaccination coverage persists at higher levels in public schools compared to private and state-subsidized schools. This occurs despite the existence of a significant correlation between the vulnerability of municipalities and vaccination coverage, indicating that lower SES is associated with reduced vaccination rates. Notably, this disparity in vaccination coverage is more pronounced in public schools. In contrast, both private and state-subsidized schools demonstrate greater equity in vaccination coverage, regardless of the SES of the municipality in which they are situated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study revealed a correlation between 9 SES indices and the COVID-19 vaccination coverage in schools belonging to 34 municipalities of the Metropolitan Area of Santiago, Chile; one of the countries with the highest rate of vaccination in the world [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. After analyzing the Spearman\u0026rsquo;s rank correlation between socioeconomic indices and COVID-19 vaccination coverage, we found a statistically significant correlation between lower SES and lower vaccination coverage. Even though inequity in vaccination coverage diminished over time along the pandemic, this inequity remains higher in public schools compared to that of private and state-subsidized schools, for all municipalities (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In general terms, our results are consistent with previous literature, indicating that vaccine coverage is lower in vulnerable populations living in poverty, having lower literacy and with a lesser educational level [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. A potential rationale for these observations may be rooted in the varied personal beliefs across different SES groups. Specifically, one study noted a discernible negative correlation between SES and skepticism towards the COVID-19 vaccine\u0026rsquo;s secondary effects and conspiracy theories, offering an insightful perspective into our findings [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to the statistically significant correlation between the vulnerability of different municipalities and the COVID-19 vaccination coverage\u0026ndash;i.e. municipalities with lower SES exhibit lower coverage\u0026ndash;, different school types exhibit distinct vaccination coverage. Thus, both public and state-subsidized schools show lower vaccination coverage than that of private schools. Although the strength of these correlations varies depending on the municipality (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), this trend is maintained along the pandemic (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, an important difference in vaccination coverage between school types, remains. Furthermore, analysis of vaccination coverage, in terms of percentages as reported by the Chilean government, uncovers significant differences across school types. However, a more alarming situation emerges when examining the raw numbers of unvaccinated children, particularly those attending schools with the lowest vaccination rates. The total number of children enrolled in public and state-subsidized schools, which demonstrate significantly lower vaccination coverage, is more than five times greater than that in private schools, with the respective figures being 873,354 and 169,898. This discrepancy highlights the critical issue of lower vaccination rates primarily among students in public and state-subsidized schools. Collectively, these two sectors account for approximately 84% of all student enrollments in the Metropolitan Area of Santiago, Chile. Considering that municipalities with lower SES are the ones having the highest population density [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], a lower vaccination coverage together with higher population density, are both key factors to consider when dealing with the higher burden of COVID-19 on these populations. Although the disparity in vaccination coverage diminishes over time, research has demonstrated that delays in vaccination schedules are associated with heightened adverse effects [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAvailable literature points to a combination of factors that may produce this uneven vaccination coverage. Among others, the lack of proper information about the importance and safety of vaccination, insufficient incentives for vaccination, religious beliefs, the negative view of pharmaceutical companies, and low trust in the government, may all have played a role in this uneven vaccination rate [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Research indicates that the impact of incentives on vaccination uptake varies across populations. Notably, monetary incentives have been found to be more effective than either encouraging messages or the promise of increased freedoms [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. A critical consideration is that children typically do not independently decide to receive vaccinations; instead, these decisions are made by their parents or caregivers. A key factor influencing vaccination decisions is the perceived risk associated with the vaccine [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Although the correlations discussed herein do not show significance when considering the adult population, it is plausible that concerns regarding vaccine risk may be amplified in the context of vaccinating children. Specifically, adults might be willing to accept the perceived risk of vaccination for themselves but hesitate to subject their children to the same perceived risks. Beyond the willingness to vaccinate, logistical barriers play a crucial role in determining vaccination uptake differences. These include the availability of vaccine doses and the accessibility of vaccination centers, which is influenced by their location, transportation options, queue lengths, and operating hours. Such factors are particularly relevant for children, who require accompaniment by an adult to vaccination sites. This necessity poses additional challenges for households where both parents work and lack childcare support, potentially impacting vaccination rates. To enhance vaccination campaigns and public policies, a more intricate examination of these contributing factors is necessary. The reliance on broad data may risk simplifying the complexities of pandemics, underlining the importance of detailed, granular data in formulating responses to not only COVID-19 but future public health crises as well.\u003c/p\u003e \u003cp\u003eOne of the limitations of our study is that the SES indices correspond to the municipal averages, so we cannot perform analyses nor extract conclusions at a granular level. In other words, assuming that an averaging SES index of the municipality would be an adequate descriptor for the whole spectrum of wealth exhibited on the municipality could be considered as a naive approach. This limitation becomes evident when trying to explain the differences in vaccination coverage between school types; we can only assume that the sub-populations that are enrolled in private schools (16%) are those that can afford the high tuition costs corresponding to the least vulnerable families in each municipality. Conversely, students enrolled in state-subsidized or in public schools are considered most vulnerable to the burden of COVID-19 (84%). Anyhow, without further socioeconomic details at an individual student level, we can only speculate about the causal roots of this inequity in vaccination coverage. Considering that COVID-19 vaccination in Chile is free of charge and governmentally orchestrated, determining the causal roots behind the lower vaccination levels noted here is crucial to develop better public policies. For example, survey studies should include questions about willingness to vaccinate children and elderly dependents of the respondent and detailed socioeconomic and educational background, vaccination throughput of each vaccination center should be analyzed in detail and correlation analysis should be performed with more detailed, granular data.\u003c/p\u003e \u003cp\u003eEven though we are unable to identify the causes of lower vaccination ratios among school-aged children in municipalities of lower, it is imperative that public policies counteract this behavior. Otherwise, the inequity in vaccination coverage will be perpetuated in future pandemics, exacerbating their impact on the more vulnerable population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eSocioeconomic status\u003c/h2\u003e \u003cp\u003eTo generate a socioeconomic profile of the municipalities in Santiago, Chile, we used nine different SES indices so to obtain a broader multi-factorial socioeconomic description. It should be noted that the reliability of all indices referenced in this study is high, as they have been sourced directly from the Government of Chile or from previously published materials. While these indices represent the most current data publicly available, it is important to acknowledge the potential for changes in the socioeconomic indices subsequent to the time of data analysis.\u003c/p\u003e \u003cp\u003eThe \u003cb\u003eSocial Priority Index (SPI)\u003c/b\u003e was published in 2019 by the Regional Ministerial Secretariat of Social Development and Family. It is a synthetic index that integrates relevant aspects of communal social development, including income, education, and health [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe \u003cb\u003eSchool Vulnerability Index (SVI)\u003c/b\u003e, published in 2021 by the National Board of School Aid and Scholarships (JUNAEB), is the ratio of the sum of the students in the first, second, and third priority ranking compared to the total school enrollment. Students are classified in priorities 1, 2, and 3 according to poverty conditions and risk of school failure. Thus, students living in lower socioeconomic conditions (Priority 1) tend to exhibit a higher risk of school failure, and thus receive the highest priority from the Board [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe Community Development Index (CDI)\u003c/b\u003e, published in 2020, is a comprehensive index that integrates three socioeconomic dimensions: Health and Social Welfare; Economy and Resources; and Education. The development of the CDI involves a meticulous process of selecting a variety of standardized and comparable indicators, aims to provide a reliable instrument for monitoring and quantifying the impact of development processes from a territorial perspective. The CDI, as well as its individual dimensions, is available for each municipality in the country [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], offering a tool for local management and decision-making. In this work, we have chosen to consider the CDI and its individual components separately. This decision stems from our aim to leverage the distinct yet complementary insights that the aggregate index and its underlying dimensions offer. The CDI provides a holistic view of community development across municipalities, facilitating broad comparisons and trend analysis. At the same time, analyzing the individual dimensions enables a deeper dive into specific areas of socioeconomic development, allowing for a nuanced understanding of strengths and challenges within each municipality. This dual approach enriches our analysis, contributing to a more comprehensive socioeconomic profile that can better inform targeted strategies for community development.\u003c/p\u003e \u003cp\u003eThe following indices are calculated as the percentage of people belonging to each category respectively for each municipality. \u003cb\u003ePoverty\u003c/b\u003e is determined by a threshold defined as a function of income level and household size. \u003cb\u003eMultidimensional Poverty\u003c/b\u003e is defined as being part of a household that cannot achieve adequate living conditions in a set of five relevant dimensions of well-being: (1) Education; (2) Health; (3) Labor and Social Security; (4) Housing and Environment; and (5) Networks and Social Cohesion. These conditions are measured through a weighted set of 15 indicators (three for each dimension). Households that accumulate deficiencies of 22.5% or more are classified as being in a situation of multidimensional poverty. The Poverty and Multidimensional Poverty indices were extracted from the National Socioeconomic Characterization Survey (CASEN) 2017, while the \u003cb\u003ePHLBS\u003c/b\u003e, which is the percentage of People in Households Lacking Basic Services, was extracted from the Social Registry of Households 2020. Both instruments are used by the Ministry of Social Development to focus on social assistance among the population. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe decision to evaluate these SES indices individually, rather than consolidating them into a single composite SES index, was driven by two primary considerations. First, analyzing the indices separately facilitates a nuanced understanding of the various dimensions of SES and their distinct impacts on vaccination coverage among school-aged children. Second, due to the complex and multifaceted nature of SES, a composite index could potentially obscure significant disparities and trends that are only discernible when these dimensions are examined on their own. This methodological approach aligns with our primary objective: to investigate the relationship between different aspects of SES and vaccination coverage in children, ensuring a more accurate and comprehensive analysis.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePandemic Data\u003c/h2\u003e \u003cp\u003eData about new cases, deaths and other aspects was published regularly by the Ministry of Science, Technology and Innovation on their freely available repository [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Specifically, we used the Daily Total National Cases to visualize the changing trends following the arrival of the different variants and sub-variants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eVaccinations\u003c/h2\u003e \u003cp\u003eEven though in Chile the COVID-19 vaccination campaign is orchestrated and conducted by the Ministry of Health, the Ministry of Education publishes vaccination coverage per grade and school on its website [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. To accurately assess the extent of vaccine coverage in each school and grade, the Ministry of Education combines its own database of school enrollments with the vaccination records from the Ministry of Health. This integration is accomplished by using the national identity number (RUT) of each student, which is the unique personal identifier in Chile. By using the RUT, they can precisely link each student\u0026rsquo;s school records with their vaccination status, ensuring a detailed and accurate understanding of the vaccination coverage across different educational institutions. To study whether the spread of different SARS-CoV-2 variants among the population might influence the vaccination process among school-age students in different municipalities in Santiago, Chile, we downloaded data published on November 15, 2021; March 1st, 2022; and May 26, 2022. By selecting these dates, we covered the spread of different SARS-CoV-2 variants: \u003cem\u003eDelta\u003c/em\u003e in November, \u003cem\u003eOmicron\u003c/em\u003e in March and \u003cem\u003eOmicron\u003c/em\u003e subvariants BA.4-BA.5 in May [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The data shows the proportion of students in each school and grade who are fully vaccinated, partially vaccinated, or not vaccinated at all. \u0026lsquo;Fully vaccinated\u0026rsquo; refers to students who have received all required doses of the COVID-19 vaccine, \u0026lsquo;partially vaccinated\u0026rsquo; indicates those who have only received some but not all of the necessary doses, and \u0026lsquo;not vaccinated\u0026rsquo; denotes students who have not received any doses of the vaccine.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eSchool metadata\u003c/h2\u003e \u003cp\u003eThe Chilean Ministry of Education provides easily accessible metadata for each educational institution on their public repository [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This metadata was used to identify public, state-subsidized and private schools in every municipality.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed on the downloaded data by programming in Python v3.1 using the SciPy v1.7.1 package [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. To measure inequity, we employed the percentile ratio p90/p40, inspired by The Palma ratio [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. In this context, \"p90\" refers to the 90th percentile, representing the mean vaccination coverage among the top 10% of municipalities with the highest vaccination rates. Conversely, \"p40\" denotes the 40th percentile, representing the mean vaccination coverage among the bottom 40% of municipalities with the lowest vaccination rates. To compute the ratio, we divided the mean vaccination coverage of the municipalities at the 90th percentile by the mean vaccination coverage of municipalities at the 40th percentile. The essence of using the p90/p40 ratio is that it highlights disparities in vaccination coverage, with maximum equity being indicated when the ratio equals 1.\u003c/p\u003e \u003cp\u003eThe calculation of the mean vaccination coverage for the highest 10% of municipalities (p90) involves aggregating the vaccination rates of municipalities that fall into the 90th percentile and then calculating the average. This figure represents the benchmark for high vaccination coverage within the sample and enables a comparison with lower-performing municipalities to assess equity in vaccination distribution.\u003c/p\u003e \u003cp\u003eSpearman\u0026rsquo;s rank-order correlation was computed using Statsmodels v0.13.1. Plots were made with Seaborn v0.11.2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003eAll data used in this research was sourced in an anonymous form.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCDI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommunity development index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMetropolitan area\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePHLBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeople in households lacking basic services\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSES\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSocioeconomic status\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSocial priority index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSVI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSchool vulnerability index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis material is based upon work supported by the U.S. Air Force Office of Scientific Research under award number FA9550-20-1-0196.\u0026nbsp;Financial support is also acknowledged to Centro Ciencia \u0026amp; Vida, FB210008, Financiamiento Basal para Centros Cient\u0026iacute;ficos y Tecnol\u0026oacute;gicos de Excelencia de ANID.\u0026nbsp;Funding sources had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.\u003c/p\u003e\n\u003cp\u003eAI use Disclosure\u003c/p\u003e\n\u003cp\u003eGenerative AI tools (ChatGPT using GPT-4) were used only to check style and grammar in some paragraphs.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eThe whole dataset as well as the python code used to perform the statistical analyses presented here are available on GitHub in the following repository.\u003c/p\u003e\n\u003cp\u003ehttps://github.com/DLab/SantiagoSchoolVax\u003c/p\u003e\n\u003cp\u003eConflicts of Interest\u003c/p\u003e\n\u003cp\u003eNone declared.\u003c/p\u003e\n\u003cp\u003eAbbreviations\u003c/p\u003e\n\u003cp\u003eCDI: Community development index\u003c/p\u003e\n\u003cp\u003eMA: Metropolitan area\u003c/p\u003e\n\u003cp\u003ePHLBS: People in households lacking basic services.\u003c/p\u003e\n\u003cp\u003eSES: Socioeconomic status\u003c/p\u003e\n\u003cp\u003eSPI: Social priority index\u003c/p\u003e\n\u003cp\u003eSVI: School vulnerability index\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eEnzo Guerrero-Araya: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Visualization, Writing.\u003c/p\u003e\n\u003cp\u003eCesar Ravello: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing.\u003c/p\u003e\n\u003cp\u003eMario Rosemblatt: Resources, Supervision, Project Administration, Writing\u003c/p\u003e\n\u003cp\u003eTom\u0026aacute;s P\u0026eacute;rez-Acle: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing.\u003c/p\u003e\n\u003cp\u003eEnzo Guerrero-Araya and Cesar Ravello share the first authorship.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRitchie, H. \u003cem\u003eet al. 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(2011).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vaccination, COVID-19, Inequality, Children vaccination","lastPublishedDoi":"10.21203/rs.3.rs-4547811/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4547811/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe burden of COVID-19 was heterogeneous, indicating that the effects of this disease are synergistic with both other non-communicable diseases and socioeconomic status (SES), highlighting its syndemic character. While the appearance of vaccines moderated the pandemic effects, their coverage was heterogeneous too, both when comparing different countries, and when comparing different populations within countries. Of note, once again SES appears to be a correlated factor.\u003c/p\u003e\n\u003cp\u003eWe analyzed publicly available data detailing the percentage of school-aged, vaccinated children in different municipalities belonging to the Metropolitan Area (MA) of Santiago, Chile. Vaccination data was compiled per school type, either public, state-subsidized, or private, at three different dates during the COVID-19 pandemic to cover the \u003cem\u003edispersion of Delta\u003c/em\u003e, \u003cem\u003eOmicron\u003c/em\u003e, and its subvariants BA.4 and BA.5. We computed the median vaccination ratio for each municipality and school type and calculated their Spearman’s rank correlation coefficient with each one of nine SES indices.\u003c/p\u003e\n\u003cp\u003eThe percentage of school-age children who received vaccinations against COVID-19 correlates with SES. This strong correlation is observed in public and state-subsidized schools, but not in private schools. Although inequity in vaccination coverage decreased over time, it remained higher among students enrolled either in public or state-subsidized schools compared to those of private schools.\u003c/p\u003e\n\u003cp\u003eAlthough available data was insufficient to explore plausible causes behind lower vaccination coverage, it is likely that a combination of factors including the lack of proper information about the importance of vaccination, the lack of incentives for children’s vaccination, low trust in the government, and limited access to vaccines for lower-income people, may all have contributed. These findings raise the need to design better strategies to overcome shortcomings in vaccination campaigns to confront future pandemics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration:\u003c/strong\u003e The present work does not involve clinical trials.\u003c/p\u003e","manuscriptTitle":"COVID-19 vaccination coverage of school-aged children in Santiago, Chile, correlates with socioeconomic status: Longitudinal observational study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-28 18:50:22","doi":"10.21203/rs.3.rs-4547811/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-18T06:01:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-16T15:20:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-03T15:33:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"225753047202718872912788629751991066498","date":"2024-07-01T14:54:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315544344977265426084570133876878800623","date":"2024-06-25T02:23:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-24T22:08:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-24T20:10:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-10T08:11:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-08T09:42:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-07T19:10:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb6dbd03-df47-4d6d-a6bc-6771f7b04863","owner":[],"postedDate":"June 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33611430,"name":"Health sciences/Health care/Public health/Epidemiology"},{"id":33611431,"name":"Health sciences/Health care/Health policy"}],"tags":[],"updatedAt":"2025-01-13T16:11:13+00:00","versionOfRecord":{"articleIdentity":"rs-4547811","link":"https://doi.org/10.1038/s41598-024-84260-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-01-09 15:57:58","publishedOnDateReadable":"January 9th, 2025"},"versionCreatedAt":"2024-06-28 18:50:22","video":"","vorDoi":"10.1038/s41598-024-84260-z","vorDoiUrl":"https://doi.org/10.1038/s41598-024-84260-z","workflowStages":[]},"version":"v1","identity":"rs-4547811","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4547811","identity":"rs-4547811","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}