1
|
Nascimento dos Santos JH, Alencar CH, Heukelbach J. SARS-CoV-2 Pandemic in a Small-Sized Municipality in Ceará State, Brazil: Temporal and Spatial Evolution. Trop Med Infect Dis 2024; 9:97. [PMID: 38787030 PMCID: PMC11125684 DOI: 10.3390/tropicalmed9050097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 04/16/2024] [Accepted: 04/23/2024] [Indexed: 05/25/2024] Open
Abstract
Data on the temporal and spatial evolution of SARS-CoV-2 and local control measures and their effects on morbidity and mortality patterns in rural Brazil are scarce. We analyzed the data from case notification systems, epidemiological investigation reports, and municipal decrees in Itapajé, a small municipality in Ceará State in northeast Brazil. For spatial and spatio-temporal analyses, cases and deaths were mapped. There were a total of 3020 cases of COVID-19, recorded between April 2020 and December 2021; 135 (4.5%) died. The cumulative incidence and mortality rates were 5650.3 cases and 252.6 deaths per 100,000 people, respectively. The index case of SARS-CoV-2 in Itapajé was diagnosed in March 2020. The first peak of cases and deaths occurred in May 2020. The second wave peaked in May 2021, with the highest number of deaths in March 2021. According to the spatial analysis, the highest density of cases and deaths occurred in the central urban areas. In these areas, there were also the clusters of highest risk according to the spatio-temporal analyses. The municipal government issued 69 decrees on restriction measures, surveillance, and the maintenance of social isolation as a response to the pandemic. The spread of the SARS-CoV-2 pandemic in Itapajé mirrored the dynamics in large metropolitan regions, going from central neighborhoods of low socio-economic status to the wealthier peripheries.
Collapse
Affiliation(s)
- Jaliana Holanda Nascimento dos Santos
- Postgraduate Course in Public Health, School of Medicine, Federal University of Ceará, Fortaleza 60.430-140, Brazil; (J.H.N.d.S.); (C.H.A.)
- Municipal Health Secretariat of Itapajé, Itapajé 62.600-000, Brazil
| | - Carlos Henrique Alencar
- Postgraduate Course in Public Health, School of Medicine, Federal University of Ceará, Fortaleza 60.430-140, Brazil; (J.H.N.d.S.); (C.H.A.)
| | - Jorg Heukelbach
- Postgraduate Course in Public Health, School of Medicine, Federal University of Ceará, Fortaleza 60.430-140, Brazil; (J.H.N.d.S.); (C.H.A.)
| |
Collapse
|
2
|
Mehrizi R, Golestani A, Malekpour MR, Karami H, Nasehi MM, Effatpanah M, Rezaee M, Shahali Z, Akbari Sari A, Daroudi R. Patterns of case fatality and hospitalization duration among nearly 1 million hospitalized COVID-19 patients covered by Iran Health Insurance Organization (IHIO) over two years of pandemic: An analysis of associated factors. PLoS One 2024; 19:e0298604. [PMID: 38394118 PMCID: PMC10889889 DOI: 10.1371/journal.pone.0298604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 01/26/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND Different populations and areas of the world experienced diverse COVID-19 hospitalization and mortality rates. Claims data is a systematically recorded source of hospitalized patients' information that could be used to evaluate the disease management course and outcomes. We aimed to investigate the hospitalization and mortality patterns and associated factors in a huge sample of hospitalized patients. METHODS In this retrospective registry-based study, we utilized claim data from the Iran Health Insurance Organization (IHIO) consisting of approximately one million hospitalized patients across various hospitals in Iran over a 26-month period. All records in the hospitalization dataset with ICD-10 codes U07.1/U07.2 for clinically/laboratory confirmed COVID-19 were included. In this study, a case referred to one instance of a patient being hospitalized. If a patient experienced multiple hospitalizations within 30 days, those were aggregated into a single case. However, if hospitalizations had longer intervals, they were considered independent cases. The primary outcomes of study were general and intensive care unit (ICU) hospitalization periods and case fatality rate (CFR) at the hospital. Besides, various demographic and hospitalization-associated factors were analyzed to derive the associations with study outcomes using accelerated failure time (AFT) and logistic regression models. RESULTS A total number of 1 113 678 admissions with COVID-19 diagnosis were recorded by IHIO during the study period, defined as 917 198 cases, including 51.9% females and 48.1% males. The 61-70 age group had the highest number of cases for both sexes. Among defined cases, CFR was 10.36% (95% CI: 10.29-10.42). The >80 age group had the highest CFR (26.01% [95% CI: 25.75-26.27]). The median of overall hospitalization and ICU days were 4 (IQR: 3-7) and 5 (IQR: 2-8), respectively. Male patients had a significantly higher risk for mortality both generally (odds ratio (OR) = 1.36 [1.34-1.37]) and among ICU admitted patients (1.12 [1.09-1.12]). Among various insurance funds, Foreign Citizens had the highest risk of death both generally (adjusted OR = 2.06 [1.91-2.22]) and in ICU (aOR = 1.71 [1.51-1.92]). Increasing age groups was a risk of longer hospitalization, and the >80 age group had the highest risk for overall hospitalization period (median ratio = 1.52 [1.51-1.54]) and at ICU (median ratio = 1.17 [1.16-1.18]). Considering Tehran as the reference province, Sistan and Balcuchestan (aOR = 1.4 [1.32-1.48]), Alborz (aOR = 1.28 [1.22-1.35]), and Khorasan Razavi (aOR = 1.24 [1.20-1.28]) were the provinces with the highest risk of mortality in hospitalized patients. CONCLUSION Hospitalization data unveiled mortality and duration associations with variables, highlighting provincial outcome disparities in Iran. Using enhanced registry systems in conjunction with other studies, empowers policymakers with evidence for optimizing resource allocation and fortifying healthcare system resilience against future health challenges.
Collapse
Affiliation(s)
- Reza Mehrizi
- National Center for Health Insurance Research, Tehran, Iran
| | - Ali Golestani
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad-Reza Malekpour
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hossein Karami
- National Center for Health Insurance Research, Tehran, Iran
| | - Mohammad Mahdi Nasehi
- National Center for Health Insurance Research, Tehran, Iran
- Pediatric Neurology Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Effatpanah
- National Center for Health Insurance Research, Tehran, Iran
- School of Medicine, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Mehdi Rezaee
- National Center for Health Insurance Research, Tehran, Iran
- Department of Orthopedics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Zahra Shahali
- National Center for Health Insurance Research, Tehran, Iran
| | - Ali Akbari Sari
- Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Rajabali Daroudi
- Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| |
Collapse
|
3
|
Laxton MR, Nightingale G, Lindgren F, Sivakumaran A, Othieno R. Extending the R number by applying hyperparameters of Log Gaussian Cox process models in an epidemiological context to provide insights into COVID-19 positivity in the City of Edinburgh and in students residing at Edinburgh University. PLoS One 2023; 18:e0291348. [PMID: 37988358 PMCID: PMC10662770 DOI: 10.1371/journal.pone.0291348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 08/29/2023] [Indexed: 11/23/2023] Open
Abstract
The impact of the COVID-19 pandemic on University students has been a topic of fiery debate and of public health research. This study demonstrates the use of a combination of spatiotemporal epidemiological models to describe the trends in COVID-19 positive cases on spatial, temporal and spatiotemporal scales. In addition, this study proposes new epidemiological metrics to describe the connectivity between observed positivity; an analogous metric to the R number in conventional epidemiology. The proposed indices, Rspatial, Rspatiotemporal and Rscaling will aim to improve the characterisation of the spread of infectious disease beyond that of the COVID-19 framework and as a result inform relevant public health policy. Apart from demonstrating the application of the novel epidemiological indices, the key findings in this study are: firstly, there were some Intermediate Zones in Edinburgh with noticeably high levels of COVID-19 positivity, and that the first outbreak during the study period was observed in Dalry and Fountainbridge. Secondly, the estimation of the distance over which the COVID-19 counts at the halls of residence are spatially correlated (or related to each other) was found to be 0.19km (0.13km to 0.27km) and is denoted by the index, Rspatial. This estimate is useful for public health policy in this setting, especially with contact tracing. Thirdly, the study indicates that the association between the surrounding community level of COVID-19 positivity (Intermediate Zones in Edinburgh) and that of the University of Edinburgh's halls of residence was not statistically significant. Fourthly, this study reveals that relatively high levels of COVID-19 positivity were observed for halls for which higher COVID-19 fines were issued (Spearman's correlation coefficient = 0.34), and separately, for halls which were non-ensuite relatively to those which were not (Spearman's correlation coefficient = 0.16). Finally, Intermediate Zones with the highest positivity were associated with student residences that experienced relatively high COVID-19 positivity (Spearman's correlation coefficient = 0.27).
Collapse
Affiliation(s)
- Megan Ruth Laxton
- School of Mathematics & Statistics, University of Glasgow, Glasgow, United Kingdom
| | - Glenna Nightingale
- School of Health in Social Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Finn Lindgren
- School of Mathematics and Statistics, University of Edinburgh, Edinburgh, United Kingdom
| | - Arjuna Sivakumaran
- NHS Lothian, Department of Public Health and Health Policy, Scotland, United Kingdom
| | - Richard Othieno
- NHS Lothian, Department of Public Health and Health Policy, Scotland, United Kingdom
| |
Collapse
|
4
|
Spatial-temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities. Sci Rep 2023; 13:4139. [PMID: 36914858 PMCID: PMC10009864 DOI: 10.1038/s41598-023-31046-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 03/06/2023] [Indexed: 03/16/2023] Open
Abstract
The COVID-19 pandemic caused impact on public health worldwide. Brazil gained prominence during the pandemic due to the magnitude of disease. This study aimed to evaluate the spatial-temporal dynamics of incidence, mortality, and case fatality of COVID-19 and its associations with social determinants in Brazilian municipalities and epidemiological week. We modeled incidence, mortality, and case fatality rates using spatial-temporal Bayesian model. "Bolsa Família Programme" (BOLSAFAM) and "proportional mortality ratio" (PMR) were inversely associated with the standardized incidence ratio (SIR), while "health insurance coverage" (HEALTHINSUR) and "Gini index" were directly associated with the SIR. BOLSAFAM and PMR were inversely associated with the standardized mortality ratio (SMR) and standardized case fatality ratio (SCFR). The highest proportion of excess risk for SIR and the SMR started in the North, expanding to the Midwest, Southeast, and South regions. The highest proportion of excess risk for the SCFR outcome was observed in some municipalities in the North region and in the other Brazilian regions. The COVID-19 incidence and mortality in municipalities that most benefited from the cash transfer programme and with better social development decreased. The municipalities with a higher proportion of non-whites had a higher risk of becoming ill and dying from the disease.
Collapse
|
5
|
Figueiredo ERL, Affonso MVDG, Jacomel RJ, Gomes FDC, Gonçalves NV, Miranda CDSC, da Silva MCF, da Silva-Júnior AF, de Melo-Neto JS. COVID-19 in the Eastern Brazilian Amazon: Incidence, Clinical Management, and Mortality by Social Determinants of Health, Symptomatology, and Comorbidities in the Xingu Health Region. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4639. [PMID: 36901646 PMCID: PMC10002208 DOI: 10.3390/ijerph20054639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/06/2022] [Accepted: 12/10/2022] [Indexed: 06/18/2023]
Abstract
This study aims to investigate the relationship between social determinants of health (SDH), incidence, and mortality to verify which sociodemographic factors, symptoms, and comorbidities predict clinical management; second, this study aims to conduct a survival analysis of individuals with COVID-19 in the Xingu Health Region. Consequently, this study adopted an ecological framework, employing secondary data of COVID-19-positive individuals from the Xingu Health Region, Pará State, Brazil. The data were obtained through the database of the State of Pará Public Health Secretary (SESPA) for the period from March 2020 to March 2021. The incidence and mortality were higher in Vitória do Xingu and Altamira. Municipalities with a higher percentage of citizens with health insurance and higher public health expenditure showed a higher incidence and mortality. A higher gross domestic product was associated with a higher incidence. Females were found to be associated with better clinical management. To live in Altamira was a risk factor for intensive care unit admission. The symptoms and comorbidities that predicted worse clinical management were dyspnea, fever, emesis, chills, diabetes, cardiac and renal diseases, obesity, and neurological diseases. There were higher incidence, mortality, and lower survival rates among the elderly. Thus, it can be concluded that SDH indicators, symptomatology, and comorbidities have implications for the incidence, mortality, and clinical management of COVID-19 in the Xingu Health Region of eastern Amazonia, Brazil.
Collapse
Affiliation(s)
| | | | | | - Fabiana de Campos Gomes
- Faculty of Medicine of São José do Rio Preto (FAMERP), São José do Rio Preto 15090-000, Brazil
| | - Nelson Veiga Gonçalves
- Laboratory of Epidemiology and Geoprocessing of Amazon, University of the state of Pará (UEPA), Belem 66050-540, Brazil
| | | | | | | | | |
Collapse
|
6
|
Sarohan AR, Edipsoy S, Özkurt ZG, Özlü C, Demir AN, Cen O. Vitamin A Deficiency, COVID-19, and Rhino-Orbital Mucormycosis (Black Fungus): An Analytical Perspective. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1436:153-166. [PMID: 37253944 DOI: 10.1007/5584_2023_774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Mucormycosis is a rare but serious opportunistic fungal disease characterized by rhino-orbito-cerebral and pulmonary involvement. It is mainly seen in people with secondary immunosuppression, isolated vitamin A deficiency, measles, and AIDS patients. It showed a rise during the second wave of the COVID-19 epidemic in the spring of 2021 in India, especially in diabetic COVID-19 patients. Vitamin A deficiency is known to cause nutritional immunodeficiency and hence leading the way to increased opportunistic fungal, bacterial, and viral infections. In the eye, it causes keratitis, night blindness, xerophthalmia, conjunctivitis, Bitot spots, keratomalacia, and retinopathy. It also causes decreased tear secretion and deterioration of the anatomical/physiological defense barrier of the eye. The negative impact of vitamin A deficiency has been previously demonstrated in measles, AIDS, and COVID-19. We think that mucormycosis in COVID-19 might be rendered by vitamin A deficiency and that vitamin A supplementation may have preventive and therapeutic values against mucormycosis and other ocular symptoms associated with COVID-19. However, any vitamin A treatment regimen needs to be based on laboratory and clinical data and supervised by medical professionals.
Collapse
Affiliation(s)
| | - Sait Edipsoy
- Department of Ophthalmology, Medicina Plus Medical Center, İstanbul, Turkey
| | | | - Can Özlü
- Department of Hematology, Kütahya Health Science University, Evliya Çelebi Education and Research Hospital, Kütahya, Turkey
| | - Ayça Nur Demir
- Faculty of Medicine, Afyonkarahisar Health Science University, Afyon, Turkey
| | - Osman Cen
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Waubonsee College, Sugar Grove, IL, USA
| |
Collapse
|
7
|
dos Santos M, Oliveira Penteado J, de Lima Brum R, da Silva Bonifácio A, Florêncio Ramires P, de Franceschi Gariboti D, Santos Cardoso RM, da Silva Júnior FMR. Ethnic/Racial Disparity in Mortality from COVID-19: Data for the Year 2020 in Brazil. SPATIAL DEMOGRAPHY 2023; 11:1-17. [PMID: 36685786 PMCID: PMC9841953 DOI: 10.1007/s40980-022-00112-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/30/2022] [Indexed: 01/18/2023]
Abstract
The study aimed to investigate ethnic/racial disparities in COVID-19 mortality in Brazilian federative units and their respective capitals in 2020. Population data and number of COVID-19 deaths were extracted by skin color (white, black, brown and indigenous) from all Brazilian states and their respective capitals. The mortality rate of COVID-19 by ethnicity in Brazilian states was higher between people from brown skin color, followed by indigenous and black. Only in one state, in the Federal District and in the federal capital, age-standardized mortality rates were higher among white's people. There is a high percentage of deaths from COVID-19 higher than expected among non-white individuals, especially in south-central states and capitals of the country. Mortality from COVID-19 affect ethnic-racial groups unevenly in Brazil and the number of excess deaths among non-whites was over 9000. Urgent government measures are needed to reduce the racial disparity in health indicators in Brazil.
Collapse
Affiliation(s)
- Marina dos Santos
- grid.411598.00000 0000 8540 6536Universidade Federal do Rio Grande - FURG, Avenida Itália, Km 8, Campus Carreiros, Rio Grande, Rio Grande do Sul 96203-900 Brazil
| | - Júlia Oliveira Penteado
- grid.411598.00000 0000 8540 6536Universidade Federal do Rio Grande - FURG, Avenida Itália, Km 8, Campus Carreiros, Rio Grande, Rio Grande do Sul 96203-900 Brazil
| | - Rodrigo de Lima Brum
- grid.411598.00000 0000 8540 6536Universidade Federal do Rio Grande - FURG, Avenida Itália, Km 8, Campus Carreiros, Rio Grande, Rio Grande do Sul 96203-900 Brazil
| | - Alicia da Silva Bonifácio
- grid.411598.00000 0000 8540 6536Universidade Federal do Rio Grande - FURG, Avenida Itália, Km 8, Campus Carreiros, Rio Grande, Rio Grande do Sul 96203-900 Brazil
| | - Paula Florêncio Ramires
- grid.411598.00000 0000 8540 6536Universidade Federal do Rio Grande - FURG, Avenida Itália, Km 8, Campus Carreiros, Rio Grande, Rio Grande do Sul 96203-900 Brazil
| | - Diuster de Franceschi Gariboti
- grid.411598.00000 0000 8540 6536Universidade Federal do Rio Grande - FURG, Avenida Itália, Km 8, Campus Carreiros, Rio Grande, Rio Grande do Sul 96203-900 Brazil
| | - Ruana Michela Santos Cardoso
- grid.411252.10000 0001 2285 6801Universidade Federal de Sergipe – UFS, Av. Marechal Rondon, S/N - Jardim Rosa Elze, São Cristóvão, SE 49100-000 Brazil
| | - Flavio Manoel Rodrigues da Silva Júnior
- grid.411598.00000 0000 8540 6536Universidade Federal do Rio Grande - FURG, Avenida Itália, Km 8, Campus Carreiros, Rio Grande, Rio Grande do Sul 96203-900 Brazil
| |
Collapse
|
8
|
Groppo MF, Groppo FC, Figueroba SR, Pereira AC. Influence of Population Size, the Human Development Index and the Gross Domestic Product on Mortality by COVID-19 in the Southeast Region of Brazil. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:14459. [PMID: 36361338 PMCID: PMC9658565 DOI: 10.3390/ijerph192114459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/31/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
UNLABELLED We evaluated the influence of population size (POP), HDI (Human Development Index) and GDP (gross domestic product) on the COVID-19 pandemic in the Southeast region of Brazil, between February 2020 and May 2021. METHODS Cases, deaths, incidence coefficient, mortality rate and lethality rate were compared among states. The cities were divided into strata according to POP, GDP, and HDI. Data were compared by Welch's ANOVA, nonlinear polynomial regression, and Spearman's correlation test (rS). RESULTS The highest incidence coefficient (p < 0.0001) and mortality rate (p < 0.05) were observed in the states of Espírito Santo and Rio de Janeiro, respectively. Until the 45th week, the higher the POP, the higher the mortality rate (p < 0.01), with no differences in the remaining period (p > 0.05). There was a strong positive correlation between POP size and the number of cases (rS = 0.92, p < 0.0001) and deaths (rS = 0.88, p < 0.0001). The incidence coefficient and mortality rate were lower (p < 0.0001) for low GDP cities. Both coefficients were higher in high- and very high HDI cities (p < 0.0001). The lethality rate was higher in the state of Rio de Janeiro (p < 0.0001), in large cities (p < 0.0001), in cities with medium GDP (p < 0.0001), and in those with high HDI (p < 0.05). CONCLUSIONS Both incidence and mortality were affected by time, with minimal influence of POP, GDP and HDI.
Collapse
Affiliation(s)
- Mônica Feresini Groppo
- Community Dentistry Department, Piracicaba Dental School, University of Campinas—UNICAMP, Av. Limeira, 901, Bairro Areião, Piracicaba 13414-903, SP, Brazil
| | - Francisco Carlos Groppo
- Department of Biosciences, Piracicaba Dental School, University of Campinas—UNICAMP, Av. Limeira, 901, Bairro Areião, Piracicaba 13414-903, SP, Brazil
| | - Sidney Raimundo Figueroba
- Department of Biosciences, Piracicaba Dental School, University of Campinas—UNICAMP, Av. Limeira, 901, Bairro Areião, Piracicaba 13414-903, SP, Brazil
| | - Antonio Carlos Pereira
- Community Dentistry Department, Piracicaba Dental School, University of Campinas—UNICAMP, Av. Limeira, 901, Bairro Areião, Piracicaba 13414-903, SP, Brazil
| |
Collapse
|
9
|
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases. Prev Med 2022; 164:107298. [PMID: 36220401 PMCID: PMC9547655 DOI: 10.1016/j.ypmed.2022.107298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 10/03/2022] [Accepted: 10/06/2022] [Indexed: 11/23/2022]
Abstract
The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%-32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%-16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%-145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes.
Collapse
|
10
|
Orellana J, Jacques N, Leventhal DGP, Marrero L, Morón-Duarte LS. Excess maternal mortality in Brazil: Regional inequalities and trajectories during the COVID-19 epidemic. PLoS One 2022; 17:e0275333. [PMID: 36264994 PMCID: PMC9584504 DOI: 10.1371/journal.pone.0275333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 09/14/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND The COVID-19 pandemic has exceeded 6 million known disease-related deaths and there is evidence of an increase in maternal deaths, especially in low- and middle-income countries. We aimed to estimate excess maternal deaths in Brazil and its macroregions as well as their trajectories in the first 15 months of the COVID-19 epidemic. METHODS This study evaluated maternal deaths from the Mortality Information System of the Ministry of Health, with excess deaths being assessed between March 2020 and May 2021 by quasi-Poisson generalized additive models adjusted for overdispersion. Observed deaths were compared to deaths expected without the pandemic, accompanied by 95% confidence intervals according to region, age group, and trimester of occurrence. Analyses were conducted in R version 3.6.1 and RStudio version 1.2.1335. RESULTS There were 3,291 notified maternal deaths during the study period, resulting in a 70% excess of deaths regardless of region, while in the North, Northeast, South and Southeast regions, excess deaths occurred regardless of age group. Excess deaths occurred in the March-May 2021 trimester regardless of region and age group. Excess deaths were observed in the Southeast region for the 25-36-year-old age group regardless of the trimester assessed, and in the North, Central-West and South regions, the only period in which excess deaths were not observed was September-November 2020. Excess deaths regardless of trimester were observed in the 37-49-year-old age group in the North region, and the South region displayed explosive behavior from March-May 2021, with a 375% excess of deaths. CONCLUSIONS Excess maternal deaths, with geographically heterogenous trajectories and consistently high patterns at the time of the epidemic's greatest impact, reflect not only the previous effect of socioeconomic inequalities and of limited access to maternal health services, but most of all the precarious management of Brazil's health crisis.
Collapse
Affiliation(s)
- Jesem Orellana
- Leônidas and Maria Deane Institute, Oswaldo Cruz Foundation, Manaus, Amazonas, Brazil
- * E-mail:
| | - Nadège Jacques
- Postgraduate Program in Epidemiology, Department of Social Medicine, Federal University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | | | - Lihsieh Marrero
- Department of Nursing, Amazonas State University, Manaus, Amazonas, Brazil
| | - Lina Sofía Morón-Duarte
- Global Institute of Clinical Excellence, Keralty, Bogotá, Distrito Capital, Colombia
- Translational Research Group, Sanitas University Foundation, Bogotá, Distrito Capital, Colombia
| |
Collapse
|
11
|
Damiri S, Shojaee A, Dehghani M, Shahali Z, Abbasi S, Daroudi R. National geographical pattern of COVID-19 hospitalization, case fatalities, and associated factors in patients covered by Iran Health Insurance Organization. BMC Public Health 2022; 22:1274. [PMID: 35773657 PMCID: PMC9243909 DOI: 10.1186/s12889-022-13649-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/16/2022] [Indexed: 11/17/2022] Open
Abstract
Background Understanding the Spatio-temporal distribution and interpersonal comparisons are important tools in etiological studies. This study was conducted to investigate the temporal and geographical distribution of COVID-19 hospitalized patients in the Iran Health Insurance Organization (IHIO) insured population (the second largest social health insurance organization) and the factors affecting their case fatality rate (CFR). Methods In this descriptive-analytical cross-sectional study, the demographic and clinical data of all insured of the IHIO who were hospitalized with COVID-19 in hospitals across the country until March 2021 was extracted from the comprehensive system of handling the inpatient documents of this organization. The Excel 2019 and GeoDA software were used for descriptive reporting and geographical distribution of variables. A multiple logistic regression model was used to estimate the Odds Ratio (OR) of death in patients with COVID-19 using STATA 14 software. Results During the first 14 months of the COVID-19 outbreak in Iran, 0.72% of the IHIO insured (303,887 individuals) were hospitalized with COVID-19. Hospitalization per 100,000 people varied from 192.51 in East Azerbaijan to 1,277.49 in Yazd province. The overall CFR in hospitalized patients was 14%. Tehran and Kohgiluyeh & BoyerAhmad provinces had the highest and lowest CFR with 19.39% and 5.19%, respectively. The highest odds of death were in those over 80 years old people (OR = 9.65), ICU-admitted (OR = 7.49), Hospitalized in governmental hospitals (OR = 2.08), Being a foreign national (OR = 1.45), hospitalized in November (OR = 1.47) and Residence in provinces such as Sistan & Baluchestan (OR = 1.47) and Razavi Khorasan (OR = 1.66) respectively. Furthermore, the odds of death were lower in females (OR = 0.81) than in males. Conclusions A sound understanding of the primary causes of COVID-19 death and severity in different groups can be the basis for developing programs focused on more vulnerable groups in order to manage the crisis more effectively and benefit from resources more efficiently. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-13649-0.
Collapse
Affiliation(s)
- Soheila Damiri
- Department of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Poursina Ave., Tehran, 1417613191, Iran
| | - Ali Shojaee
- Department of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Poursina Ave., Tehran, 1417613191, Iran.,National Center for Health Insurance Research, Tehran, Iran
| | - Mohsen Dehghani
- Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Zahra Shahali
- National Center for Health Insurance Research, Tehran, Iran
| | | | | |
Collapse
|
12
|
Associations between COVID-19 Pandemic, Lockdown Measures and Human Mobility: Longitudinal Evidence from 86 Countries. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19127317. [PMID: 35742567 PMCID: PMC9223807 DOI: 10.3390/ijerph19127317] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/12/2022] [Accepted: 06/13/2022] [Indexed: 12/18/2022]
Abstract
Recognizing an urgent need to understand the dynamics of the pandemic’s severity, this longitudinal study is conducted to explore the evolution of complex relationships between the COVID-19 pandemic, lockdown measures, and social distancing patterns in a diverse set of 86 countries. Collecting data from multiple sources, a structural equation modeling (SEM) technique is applied to understand the interdependencies between independent variables, mediators, and dependent variables. Results show that lockdown and confinement measures are very effective to reduce human mobility at retail and recreation facilities, transit stations, and workplaces and encourage people to stay home and thereby control COVID-19 transmission at critical times. The study also found that national contexts rooted in socioeconomic and institutional factors influence social distancing patterns and severity of the pandemic, particularly with regard to the vulnerability of people, treatment costs, level of globalization, employment distribution, and degree of independence in society. Additionally, this study portrayed a mutual relationship between the COVID-19 pandemic and human mobility. A higher number of COVID-19 confirmed cases and deaths reduces human mobility and the countries with reduced personal mobility have experienced a deepening of the severity of the pandemic. However, the effect of mobility on pandemic severity is stronger than the effect of pandemic situations on mobility. Overall, the study displays considerable temporal changes in the relationships between independent variables, mediators, and dependent variables considering pandemic situations and lockdown regimes, which provides a critical knowledge base for future handling of pandemics. It has also accommodated some policy guidelines for the authority to control the transmission of COVID-19.
Collapse
|
13
|
Feng C. Spatial-temporal generalized additive model for modeling COVID-19 mortality risk in Toronto, Canada. SPATIAL STATISTICS 2022; 49:100526. [PMID: 34249608 PMCID: PMC8257405 DOI: 10.1016/j.spasta.2021.100526] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 06/03/2021] [Accepted: 06/25/2021] [Indexed: 06/13/2023]
Abstract
This article presents a spatial-temporal generalized additive model for modeling geo-referenced COVID-19 mortality data in Toronto, Canada. A range of factors and spatial-temporal terms are incorporated into the model. The non-linear and interactive effects of the neighborhood-level factors, i.e., population density and average of income, are modeled as a two-dimensional spline smoother. The change of spatial pattern over time is modeled as a three-dimensional tensor product smoother. By fitting this model, the space-time effect can uncover the underlying spatial-temporal pattern that is not explained by the covariates. The performance of the modeling method based on the individual data is also compared to the modeling methods based on the aggregated data in terms of in-sample and out-of-sample predictive checking. The results suggest that the individual-level based analysis provided a better overall model fit and higher predictive accuracy for detecting epidemic peaks in this application as compared to the analysis based on the aggregated data.
Collapse
Affiliation(s)
- Cindy Feng
- Department of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada, B3H 1V7
| |
Collapse
|
14
|
de Souza APG, Mota CMDM, Rosa AGF, de Figueiredo CJJ, Candeias ALB. A spatial-temporal analysis at the early stages of the COVID-19 pandemic and its determinants: The case of Recife neighborhoods, Brazil. PLoS One 2022; 17:e0268538. [PMID: 35580093 PMCID: PMC9113566 DOI: 10.1371/journal.pone.0268538] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 04/30/2022] [Indexed: 12/11/2022] Open
Abstract
The outbreak of COVID-19 has led to there being a worldwide socio-economic crisis, with major impacts on developing countries. Understanding the dynamics of the disease and its driving factors, on a small spatial scale, might support strategies to control infections. This paper explores the impact of the COVID-19 on neighborhoods of Recife, Brazil, for which we examine a set of drivers that combines socio-economic factors and the presence of non-stop services. A three-stage methodology was conducted by conducting a statistical and spatial analysis, including clusters and regression models. COVID-19 data were investigated concerning ten dates between April and July 2020. Hotspots of the most affected regions and their determinant effects were highlighted. We have identified that clusters of confirmed cases were carried from a well-developed neighborhood to socially deprived areas, along with the emergence of hotspots of the case-fatality rate. The influence of age-groups, income, level of education, and the access to essential services on the spread of COVID-19 was also verified. The recognition of variables that influence the spatial spread of the disease becomes vital for pinpointing the most vulnerable areas. Consequently, specific prevention actions can be developed for these places, especially in heterogeneous cities.
Collapse
Affiliation(s)
| | - Caroline Maria de Miranda Mota
- Programa de Pós-graduação em Engenharia de Produção, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil
- Departamento de Engenharia de Produção, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil
- * E-mail:
| | - Amanda Gadelha Ferreira Rosa
- Programa de Pós-graduação em Engenharia de Produção, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil
| | | | | |
Collapse
|
15
|
Bustos Carrillo FA, Mercado BL, Monterrey JC, Collado D, Saborio S, Miranda T, Barilla C, Ojeda S, Sanchez N, Plazaola M, Laguna HS, Elizondo D, Arguello S, Gajewski AM, Maier HE, Latta K, Carlson B, Coloma J, Katzelnick L, Sturrock H, Balmaseda A, Kuan G, Gordon A, Harris E. Epidemics of chikungunya, Zika, and COVID-19 reveal bias in case-based mapping. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2021.07.23.21261038. [PMID: 34341804 PMCID: PMC8328077 DOI: 10.1101/2021.07.23.21261038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Accurate tracing of epidemic spread over space enables effective control measures. We examined three metrics of infection and disease in a pediatric cohort (N≈3,000) over two chikungunya and one Zika epidemic, and in a household cohort (N=1,793) over one COVID-19 epidemic in Managua, Nicaragua. We compared spatial incidence rates (cases/total population), infection risks (infections/total population), and disease risks (cases/infected population). We used generalized additive and mixed-effects models, Kulldorf's spatial scan statistic, and intracluster correlation coefficients. Across different analyses and all epidemics, incidence rates considerably underestimated infection and disease risks, producing large and spatially non-uniform biases distinct from biases due to incomplete case ascertainment. Infection and disease risks exhibited distinct spatial patterns, and incidence clusters inconsistently identified areas of either risk. While incidence rates are commonly used to infer infection and disease risk in a population, we find that this can induce substantial biases and adversely impact policies to control epidemics.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | - Sergio Ojeda
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Nery Sanchez
- Sustainable Sciences Institute, Managua, Nicaragua
| | | | | | | | | | | | | | - Krista Latta
- University of Michigan, Ann Arbor, Michigan, USA
| | | | - Josefina Coloma
- University of California, Berkeley, Berkeley, California, USA
| | - Leah Katzelnick
- University of California, Berkeley, Berkeley, California, USA
| | - Hugh Sturrock
- University of California, San Francisco, San Francisco, California, USA
- Locational, Poole, UK
| | - Angel Balmaseda
- Sustainable Sciences Institute, Managua, Nicaragua
- Ministry of Health, Managua, Nicaragua
| | - Guillermina Kuan
- Sustainable Sciences Institute, Managua, Nicaragua
- Ministry of Health, Managua, Nicaragua
| | | | - Eva Harris
- University of California, Berkeley, Berkeley, California, USA
| |
Collapse
|
16
|
Silva AVFG, Menezes D, Moreira FRR, Torres OA, Fonseca PLC, Moreira RG, Alves HJ, Alves VR, Amaral TMDR, Coelho AN, Saraiva Duarte JM, da Rocha AV, de Almeida LGP, de Araújo JLF, de Oliveira HS, de Oliveira NJC, Zolini C, de Sousa JH, de Souza EG, de Souza RM, Ferreira LDL, Lehmkuhl Gerber A, Guimarães APDC, Maia PHS, Marim FM, Miguita L, Monteiro CC, Neto TS, Pugêdo FSF, Queiroz DC, Queiroz DNAC, Resende-Moreira LC, Santos FM, Souza EFC, Voloch CM, Vasconcelos AT, de Aguiar RS, de Souza RP. Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil. Front Microbiol 2022; 13:799713. [PMID: 35197952 PMCID: PMC8859412 DOI: 10.3389/fmicb.2022.799713] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 01/07/2022] [Indexed: 11/18/2022] Open
Abstract
The COVID-19 pandemic has created an unprecedented need for epidemiological monitoring using diverse strategies. We conducted a project combining prevalence, seroprevalence, and genomic surveillance approaches to describe the initial pandemic stages in Betim City, Brazil. We collected 3239 subjects in a population-based age-, sex- and neighborhood-stratified, household, prospective; cross-sectional study divided into three surveys 21 days apart sampling the same geographical area. In the first survey, overall prevalence (participants positive in serological or molecular tests) reached 0.46% (90% CI 0.12–0.80%), followed by 2.69% (90% CI 1.88–3.49%) in the second survey and 6.67% (90% CI 5.42–7.92%) in the third. The underreporting reached 11, 19.6, and 20.4 times in each survey. We observed increased odds to test positive in females compared to males (OR 1.88 95% CI 1.25–2.82), while the single best predictor for positivity was ageusia/anosmia (OR 8.12, 95% CI 4.72–13.98). Thirty-five SARS-CoV-2 genomes were sequenced, of which 18 were classified as lineage B.1.1.28, while 17 were B.1.1.33. Multiple independent viral introductions were observed. Integration of multiple epidemiological strategies was able to adequately describe COVID-19 dispersion in the city. Presented results have helped local government authorities to guide pandemic management.
Collapse
Affiliation(s)
| | - Diego Menezes
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | | | - Paula Luize Camargos Fonseca
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Rennan Garcias Moreira
- Centro de Laboratórios Multiusuários, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Hugo José Alves
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | | | | | - Júlia Maria Saraiva Duarte
- Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | | | - João Locke Ferreira de Araújo
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | | | - Camila Zolini
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Jôsy Hubner de Sousa
- Programa de Pós-graduação em Biologia Celular, Departamento de Morfologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Rafael Marques de Souza
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Luciana de Lima Ferreira
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | | | | | - Fernanda Martins Marim
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Lucyene Miguita
- Departamento de Patologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | | | | | - Daniel Costa Queiroz
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Luciana Cunha Resende-Moreira
- Departamento de Botânica, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Franciele Martins Santos
- Programa de Pós-graduação em Biologia Celular, Departamento de Morfologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Carolina Moreira Voloch
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Renato Santana de Aguiar
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Instituto D'Or de Pesquisa e Ensino (IDOR), Rio de Janeiro, Brazil
| | - Renan Pedra de Souza
- Programa de Pós Graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| |
Collapse
|
17
|
Lima EEC, Vilela EA, Peralta A, Rocha M, Queiroz BL, Gonzaga MR, Piscoya-Díaz M, Martinez-Folgar K, García-Guerrero VM, Freire FHMA. Investigating regional excess mortality during 2020 COVID-19 pandemic in selected Latin American countries. GENUS 2021; 77:30. [PMID: 34744175 PMCID: PMC8564791 DOI: 10.1186/s41118-021-00139-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 10/11/2021] [Indexed: 11/10/2022] Open
Abstract
In this paper, we measure the effect of the 2020 COVID-19 pandemic wave at the national and subnational levels in selected Latin American countries that were most affected: Brazil, Chile, Ecuador, Guatemala, Mexico, and Peru. We used publicly available monthly mortality data to measure the impacts of the pandemic using excess mortality for each country and its regions. We compare the mortality, at national and regional levels, in 2020 to the mortality levels of recent trends and provide estimates of the impact of mortality on life expectancy at birth. Our findings indicate that from April 2020 on, mortality exceeded its usual monthly levels in multiple areas of each country. In Mexico and Peru, excess mortality was spreading through many areas by the end of the second half of 2020. To a lesser extent, we observed a similar pattern in Brazil, Chile, and Ecuador. We also found that as the pandemic progressed, excess mortality became more visible in areas with poorer socioeconomic and sanitary conditions. This excess mortality has reduced life expectancy across these countries by 2-10 years. Despite the lack of reliable information on COVID-19 mortality, excess mortality is a useful indicator for measuring the effects of the coronavirus pandemic, especially in the context of Latin American countries, where there is still a lack of good information on causes of death in their vital registration systems. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1186/s41118-021-00139-1.
Collapse
Affiliation(s)
| | | | - Andrés Peralta
- Public Health Institute, Pontifical Catholic University of Ecuador (PUCE) – Ecuador, Quito, Ecuador
| | | | | | - Marcos R. Gonzaga
- Departamento de Demografia e Ciências Atuariais, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | | | - Kevin Martinez-Folgar
- Urban Health Collaborative & Department of Epidemiology and Biostatistics, Dornsife School of Public
Health, Drexel University, Philadelphia, PA USA
| | | | - Flávio H. M. A. Freire
- Departamento de Demografia e Ciências Atuariais, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| |
Collapse
|
18
|
Paula-Júnior WD, Nascimento RCRMD, Matiles RS, Lima-Neto FFD, Leles MCR, Guimarães HN, Grabe-Guimarães A. COVID-19 in medium-sized municipalities in the 14 health macro-regions of Minas Gerais, Brazil. Braz J Med Biol Res 2021; 54:e11191. [PMID: 34431872 PMCID: PMC8389611 DOI: 10.1590/1414-431x2021e11191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 06/22/2021] [Indexed: 11/22/2022] Open
Abstract
The present study focused on the scenario of confirmed cases of SARS-CoV-2 infection in the state of Minas Gerais (MG), Brazil, from March 2020 to March 2021. We evaluated the evolution of COVID-19 prevalence and death in one municipality from each of the 14 health macro-regions of MG state. Socio-demographic characteristics and variables related to the municipalities were analyzed. The raw dataset used in this study was freely sourced from the website Brasil.io. From the raw dataset, two time series were extracted: the cumulative confirmed cases of COVID-19 and cumulative death counts, and they were compared to the state data using a nowcasting approach. In order to make time series comparisons possible, all data was normalized per 100,000 inhabitants. When analyzing in light of colored wave code interventions initiated in August 2020 in MG, for the majority of the municipalities, there was an absence of clear influence on prevalence and deaths. The national holidays in the first semester of 2020 had a small impact on the COVID-19 prevalence of the municipalities, but the holidays in the second semester of 2020 and beginning of 2021 caused important impacts on COVID-19 prevalence. The low number of ICU beds in some municipalities contributed to the higher number of deaths. The analysis showed here is expected to contribute to the improvement of decision making of the MG government, as it opened a huge possibility to have the total macro-regions and state data analyzed.
Collapse
Affiliation(s)
- W de Paula-Júnior
- Universidade Estadual de Montes Claros, Montes Claros, MG, Brasil.,Programa de Pós-graduação em Ciências Farmacêuticas, Escola de Farmácia, Universidade Federal de Ouro Preto, Ouro Preto, MG, Brasil
| | - R C R M do Nascimento
- Programa de Pós-graduação em Ciências Farmacêuticas, Escola de Farmácia, Universidade Federal de Ouro Preto, Ouro Preto, MG, Brasil
| | - R S Matiles
- Faculdade de Ciências Gerenciais, Manhuaçu, MG, Brasil
| | - F F de Lima-Neto
- Universidade Estadual de Montes Claros, Montes Claros, MG, Brasil
| | - M C R Leles
- Universidade Federal de São João Del-Rei, Campus Alto Paraopeba, Ouro Branco, MG, Brasil
| | - H N Guimarães
- Escola de Engenharia, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil
| | - A Grabe-Guimarães
- Programa de Pós-graduação em Ciências Farmacêuticas, Escola de Farmácia, Universidade Federal de Ouro Preto, Ouro Preto, MG, Brasil
| |
Collapse
|
19
|
The COVID-19 Vaccination Strategy in Brazil-A Case Study. EPIDEMIOLGIA (BASEL, SWITZERLAND) 2021; 2:338-359. [PMID: 36417230 PMCID: PMC9620893 DOI: 10.3390/epidemiologia2030026] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Revised: 07/23/2021] [Accepted: 08/03/2021] [Indexed: 12/14/2022]
Abstract
Brazil is among the countries which have faced two devastating infection waves of COVID-19 in the past year. Despite the fact the country has one of the world's leading immunization programs, Brazil only slowly established a national COVID-19 vaccination strategy and campaign. This case study is based on an integrative review of primary and secondary literature sources. Different search strategies on Medline and Google Scholar were performed for the case presentation, for the management and outcome of the COVID-19 outbreak and for the state of the COVID-19 vaccination program. Official documents from the Brazilian Ministry of Health, the website of the World Health Organization and pharmaceutical companies were also reviewed. Searches were limited to English, French, German, Portuguese and Spanish. This article describes the Brazilian COVID-19 vaccination campaign and the drivers and barriers to its implementation; and evaluates further investigations needed to have a conclusive overview over the constantly evolving situation. Healthcare inequalities, which were widened during the pandemic, a lack of coordination at the federal level, the absence of federal government support for scientific research and the lack of endorsement and commitment to the mitigation of the COVID-19 pandemic set the country's COVID-19 vaccination campaign off to a challenging start. However, Brazil had a well-developed primary care system and national vaccination program prior to the pandemic, which are both important facilitators. At the time of writing, six vaccines are currently available in the country, and the program is advancing. The scientific community needs to continue to investigate the country's vaccination strategy and its implementation to make sure that maximum effort is undertaken for the health of the Brazilian population.
Collapse
|
20
|
Madden JM, More S, Teljeur C, Gleeson J, Walsh C, McGrath G. Population Mobility Trends, Deprivation Index and the Spatio-Temporal Spread of Coronavirus Disease 2019 in Ireland. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:6285. [PMID: 34200681 PMCID: PMC8296107 DOI: 10.3390/ijerph18126285] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 06/02/2021] [Accepted: 06/04/2021] [Indexed: 12/16/2022]
Abstract
Like most countries worldwide, the coronavirus disease (COVID-19) has adversely affected Ireland. The aim of this study was to (i) investigate the spatio-temporal trend of COVID-19 incidence; (ii) describe mobility trends as measured by aggregated mobile phone records; and (iii) investigate the association between deprivation index, population density and COVID-19 cases while accounting for spatial and temporal correlation. Standardised incidence ratios of cases were calculated and mapped at a high spatial resolution (electoral division level) over time. Trends in the percentage change in mobility compared to a pre-COVID-19 period were plotted to investigate the impact of lockdown restrictions. We implemented a hierarchical Bayesian spatio-temporal model (Besag, York and Mollié (BYM)), commonly used for disease mapping, to investigate the association between covariates and the number of cases. There have been three distinct "waves" of COVID-19 cases in Ireland to date. Lockdown restrictions led to a substantial reduction in human movement, particularly during the 1st and 3rd wave. Despite adjustment for population density (incidence ratio (IR) = 1.985 (1.915-2.058)) and the average number of persons per room (IR = 10.411 (5.264-22.533)), we found an association between deprivation index and COVID-19 incidence (IR = 1.210 (CI: 1.077-1.357) for the most deprived quintile compared to the least deprived). There is a large range of spatial heterogeneity in COVID-19 cases in Ireland. The methods presented can be used to explore locally intensive surveillance with the possibility of localised lockdown measures to curb the transmission of infection, while keeping other, low-incidence areas open. Our results suggest that prioritising densely populated deprived areas (that are at increased risk of comorbidities) during vaccination rollout may capture people that are at risk of infection and, potentially, also those at increased risk of hospitalisation.
Collapse
Affiliation(s)
- Jamie M. Madden
- Centre for Veterinary Epidemiology and Risk Analysis (CVERA), School of Veterinary Medicine, University College Dublin, D04 W6F6 Dublin, Ireland; (S.M.); (G.M.)
| | - Simon More
- Centre for Veterinary Epidemiology and Risk Analysis (CVERA), School of Veterinary Medicine, University College Dublin, D04 W6F6 Dublin, Ireland; (S.M.); (G.M.)
| | - Conor Teljeur
- Health Technology Assessment Directorate, Health Information and Quality Authority, D07 E98Y Dublin, Ireland;
| | - Justin Gleeson
- National Institute for Regional and Spatial Analysis, National University of Ireland Maynooth, W23 F2H6 Kildare, Ireland;
| | - Cathal Walsh
- Health Research Institute and MACSI, University of Limerick, V94 T9PX Limerick, Ireland;
| | - Guy McGrath
- Centre for Veterinary Epidemiology and Risk Analysis (CVERA), School of Veterinary Medicine, University College Dublin, D04 W6F6 Dublin, Ireland; (S.M.); (G.M.)
| |
Collapse
|