Suchergebnisse

ObjectivesAdministrative data are primarily collected for operational processes and these processes can lead to sources of bias that may not be adequately considered by researchers. We provide a framework to help understand how biases might arise from using linked administrative data, and hopefully aid future study designs.
ApproachWe developed the conceptual framework based on the team's experiences with the 100 Million Brazilian Cohort (100MCohort) which contains records of more than 131 million people whose families applied for social assistance between 2001 and 2018, linked to other administrative data sources. We provide examples from the 100MCohort of where and how in the linkage process different forms of bias could arise. We make recommendations on how biases might be addressed using commonly available external data.
ResultsThe conceptual framework covers the whole data generating process from people and events occurring in the population through to deriving variables for analysis. The framework comprises three distinct stages: 1) Recording and registration of events in administrative systems such as Brazil's Mortality Information System (SIM) and the Hospital Information System (SIH); 2) Linkage of different data sources, for example using exact matching via the Social Identification Number (NIS) in Brazil's CadÚnico database or linkage algorithms; 3) Cleaning and coding data used both for analysis and linkage. The biases arising from linkage can be better understood by applying theory and making additional metadata available.
ConclusionMaximising the potential of administrative data for research requires a better understanding of how biases arise. This is best achieved by considering the entire data generating process, and better communication among all those involved in the data collection and linkage processes.

IntroductionHealth inequalities in Brazil have deepened on Covid-19 pandemic, and the most vulnerable people were the more affected. A multidisciplinary team from Cidacs/Fiocruz Bahia developed a Social Disparities Index for Covid-19 (IDS-COVID-19) to support the evaluation of effects of health inequalities on the pandemic in Brazil. Public Involvement and Engagement were the pillars of this research because they allowed us to access first hand experiences about the social context in our country.
ObjectivesThis paper aims to describe our Public Involvement and Engagement experience by analysing our challenges, strategies, activities, results, and lessons learned during the construction of IDS-COVID-19.
MethodsThe basis of the IDS-Covid-19 public engagement model was the participation of different social groups through methods and techniques that allow dialogue. Several activities and communication products supported the continuous interactions. Another guideline was the inclusion and the welcoming of participants from the beginning of the project to ensure that the participant's contributions could drive decision-making about the research.
ResultsParticipants made several contributions to the research as a new layer of information to the Index, and improvements were made to the interactive panel. They also compromised to support the dissemination and use of the product. Eight representatives of community groups and 29 policymakers participated in our engagement activities during the project. More than 500 people were in our open webinars. In addition, more than 140 news items about IDS-Covid-19 were published in national and international media.
ConclusionsWe highlight as lessons learned the adaptation of some dissemination formats to the public, and the necessity of being flexible and accessible to participants. We strengthened the relationship with relevant stakeholders by exploring individual conversations by phone, WhatsApp, email, and interviews to produce a documentary that registered this whole experience. Cidacs/Fiocruz Bahia has also embedded public engagement and involvement in the study agenda.

ObjectivesMitigating the socioeconomic determinants of Tuberculosis (TB) and systematic screening of contacts and high-risk groups are targets of The World Health Organization (WHO) End TB Strategy by 2035. Our aim was to link socioeconomic information to TB datasets to inform policy makers in Brazil and contribute to addressing current challenges.
ApproachFollowing a signed technical cooperation agreement with the Ministry of Health (MoH), we linked nationwide data on 1.405.682 registries of TB diagnosed between 2004 and 2019 in Brazil to 131.697.800 demographic and socioeconomic registries from the 100 Million Brazilian Cohort (2001-2018) previously linked to nationwide mortality data. We established close links with TB managers to understand the database, clean and deduplicate registries and to analyse the data. We took advantage of the data structure, to set up a cohort of household contacts of TB patients and produce estimates of TB incidence by subgroups of demographic and socioeconomic characteristics.
ResultsThe interaction of the MoH was effective and facilitated by a robust TB Programme in the country. 567.999 (40,41%) TB cases were linked to the 100 Million Brazilian Cohort with high specificity (93.6%) and sensitivity (94.6%). Using family identifiers, we established the first TB case within a family unit (i.e., primary case) and followed their household contacts up to 15 years. We found the TB incidence among household contacts to be 427.8/100.000 person-years (95%CI 419.1-436.8). In the first year following the identification of the primary case, there was higher cumulative incidence among household contacts under 5 years of age, which was followed by a plateau of cases in this age group. Cummulative incidence in the other age groups presented a constant increase over time.
ConclusionThe close collaboration with the MoH, the development of an effective linkage algorithm and the availability of large socioeconomic data allowed for a unique analysis of the high incidence of TB among household contacts. Findings reinforce need for constant dialogue among stakeholders to strengthen case detection by primary health care.

OBJECTIVE: To describe and assess currently used area-based measures of deprivation in Brazil for health research, to the purpose of informing the development of a future small area deprivation index. METHODS: We searched five electronic databases and seven websites of Brazilian research institutions and governmental agencies. Inclusion criteria were: studies proposing measures of deprivation for small areas (i.e., finer geography than country-level) in Brazil, published in English, Portuguese or Spanish. After data-extraction, results were tabulated according to the area level the deprivation measure was created for and to the dimensions of deprivation or poverty included in the measures. A narrative synthesis approach was used to summarize the measures available, highlighting their utility for public health research. RESULTS: A total of 7,199 records were retrieved, 126 full-text articles were assessed after inclusion criteria and a final list of 30 articles was selected. No small-area deprivation measures that have been applied to the whole of Brazil were found. Existing measures were mainly used to study infectious and parasitic diseases. Few studies used the measures to assess inequalities in mortality and no studies used the deprivation measure to evaluate the impact of social programs. CONCLUSIONS: No up-to-date small area-based deprivation measure in Brazil covers the whole country. There is a need to develop such an index for Brazil to measure and monitor inequalities in health and mortality, particularly to assess progress in Brazil against the Sustainable Development Goal targets for different health outcomes, showing progress by socioeconomic groups.

ObjectivesCovid-19 databases have detailed information about each affected person in Brazil, but it has flaws in counting the number of cases, which are underreported. We aimed to construct and correct the cases dataset by linking different sources of data observations to study the pandemic evolution in Brazilian municipalities.
ApproachUsing the electronic Unified Health System (e-SUS), a public and governmental database, we calculated the pandemic curves of COVID-19 cases. We applied the following approaches to investigate data anomalies a) to perform a descriptive analysis and compare these results with a non-governmental database using Dynamic Time Warping distance; b) to verify and correct municipalities data anomalies linking to other public governmental database namely National Council of Health Secretaries (CONASS) with e-SUS. c) To apply a K-means DTW Barycenter Averaging in clustering analysis to describe the general behaviors of pandemic in Brazilian Municipalities.
ResultsAround 10% records of cases in the e-SUS public governmental database were underreported. After the linkage and the data updating procedure, the time-dependent clustering analysis presents no anomalies and more interpretable results. The clustering analysis provided eight different behaviors of COVID-19 curves of cases. The degree of intensity for prevalence and incidence rates were identified according to eight clusters from the lowest to highest.
ConclusionsUsing the matching procedure based on Dynamic Time Warping distance to correct the municipalities unreported cases, we provided a richer dataset to support a clustering time dependent analysis to characterize the Pandemic evolution in Brazil. These results may be explored in future deprivation social studies.

OBJECTIVE: To describe and assess currently used area-based measures of deprivation in Brazil for health research, to the purpose of informing the development of a future small area deprivation index. METHODS: We searched five electronic databases and seven websites of Brazilian research institutions and governmental agencies. Inclusion criteria were: studies proposing measures of deprivation for small areas (i.e., finer geography than country-level) in Brazil, published in English, Portuguese or Spanish. After data-extraction, results were tabulated according to the area level the deprivation measure was created for and to the dimensions of deprivation or poverty included in the measures. A narrative synthesis approach was used to summarize the measures available, highlighting their utility for public health research. RESULTS: A total of 7,199 records were retrieved, 126 full-text articles were assessed after inclusion criteria and a final list of 30 articles was selected. No small-area deprivation measures that have been applied to the whole of Brazil were found. Existing measures were mainly used to study infectious and parasitic diseases. Few studies used the measures to assess inequalities in mortality and no studies used the deprivation measure to evaluate the impact of social programs. CONCLUSIONS: No up-to-date small area-based deprivation measure in Brazil covers the whole country. There is a need to develop such an index for Brazil to measure and monitor inequalities in health and mortality, particularly to assess progress in Brazil against the Sustainable Development Goal targets for different health outcomes, showing progress by socioeconomic groups

ABSTRACT OBJECTIVE To describe and assess currently used area-based measures of deprivation in Brazil for health research, to the purpose of informing the development of a future small area deprivation index. METHODS We searched five electronic databases and seven websites of Brazilian research institutions and governmental agencies. Inclusion criteria were: studies proposing measures of deprivation for small areas (i.e., finer geography than country-level) in Brazil, published in English, Portuguese or Spanish. After data-extraction, results were tabulated according to the area level the deprivation measure was created for and to the dimensions of deprivation or poverty included in the measures. A narrative synthesis approach was used to summarize the measures available, highlighting their utility for public health research. RESULTS A total of 7,199 records were retrieved, 126 full-text articles were assessed after inclusion criteria and a final list of 30 articles was selected. No small-area deprivation measures that have been applied to the whole of Brazil were found. Existing measures were mainly used to study infectious and parasitic diseases. Few studies used the measures to assess inequalities in mortality and no studies used the deprivation measure to evaluate the impact of social programs. CONCLUSIONS No up-to-date small area-based deprivation measure in Brazil covers the whole country. There is a need to develop such an index for Brazil to measure and monitor inequalities in health and mortality, particularly to assess progress in Brazil against the Sustainable Development Goal targets for different health outcomes, showing progress by socioeconomic groups.

ObjectiveBrazil is one of the most unequal countries in the world. We aimed to create a Social Disparities Index for Covid-19 (SDI-Covid-19) using linked administrative data to understand the role of inequalities in the COVID-19 pandemic to target social and health policies.
ApproachUsing linked administrative data (2010 Census and National Registry of Health Establishments) we selected municipal indicators for three domains: a) Brazilian Deprivation Index; b) % black/brown/indigenous, % people living in housing with density >2 person/room, % poor older people as sociodemographic; c) ICU beds and respirators rates weighted by distance to the health region headquarters as access to health service. A z-score weighted by the population estimated each indicator within the domains. The domains were combined by simple average of the z-scores and classified in quintiles (1-very low to 5-very high). Other methods (TRI, Macharia et al)1 found similar estimative.
ResultsThe SDI-COVID-19 estimated for the three moments of the pandemic (before (T0), first (T1) and second peak (T2)) in Brazil showed that municipalities belonging to the North and Northeast regions had worse SDI-Covid-19 compared to municipalities in the Midwest, Southeast, and South regions of the country. More than 97% of the municipalities in the North and Northeast regions had high and very high SDI in the three estimated periods. There was an increase of 46% in the number of municipalities in the Midwest region with high and very high SDI in T1 and 33% in T2 when compared to T0. Otherwise, we observed an increase of municipalities with very low and low SDI in T1 and T2 in the Southeast and South regions
ConclusionsThe deterministic linkage of administrative data allowed to build the SDI-COVID-19. This index identified the most vulnerable municipalities in the North and Northeast regions in contrast of municipalities in the Southeast and South regions of Brazil with lower inequalities during the pandemic. Findings can target policies to those areas.

Growth is an important marker of child health and development. It is related to aspects such as social-economic conditions, being affected by social inequalities. Race is a social construct that functions as an essential tool of racism. It creates social hierarchy, resulting in segregation, different quality and access to health care, and unequal distributions of social determinants on health. Understanding the effects of ethno-racial inequalities on growth trajectories is essential to improve children development and well-being. In the study we investigated child growth according to maternal ethno-racial group using a nationwide Brazilian database. Data were obtained via linkage of the CIDACS Birth Cohort and the Brazilian Food the Nutrition Surveillance System. It included 4,090,271 children under 5 years old, born at term, followed-up between 2008 and 2017. We used mixed-effects model to estimate both original and standardized forms of length/height and weight trajectories. Results pointed out to growth differences among the racial groups, concerning both markers. Children born to Indigenous mothers presented the most critical situation, followed by those born to Parda, Asian-descent, and Black mothers. The strengthening of policies aimed at protecting Indigenous children should be urgently undertaken to address systematic ethno-racial health inequalities. Additionally, these findings may help policymakers to achieve the United Nation's 2030 Sustainable Development Goals (eradication of hunger and all forms of malnutrition).

Objective In Brazil, national estimates of childhood malnutrition have not been updated since 2006. The use of health information systems is an important complementary data source for analysing time trends on health and nutrition. This study aimed to examine temporal trends and socio-demographic inequalities in the prevalence of malnutrition in children attending primary health care services between 2009 and 2017. Design Time trends study based on data from Brazil's Food and Nutrition Surveillance System. Malnutrition prevalence (stunting, wasting, overweight and double burden) was annually estimated by socio-demographic variables. Prais-Winsten regression models were used to analyse time trends. Annual percent change (APC) and 95 % CI were calculated. Setting Primary health care services, Brazil. Participants Children under 5 years old. Results In total, 15,239,753 children were included. An increase in the prevalence of overweight (APC = 3·4 %; P = 0·015) and a decline in the prevalence of wasting (-6·2 %; P = 0·002) were observed. The prevalence of stunting (-3·2 %, P = 0·359) and double burden (-1·4 %, P = 0·630) had discrete and non-significant reductions. Despite the significant reduction in the prevalence of undernutrition among children in the most vulnerable subgroups (black, conditional cash transfer's recipients and residents of poorest and less developed areas), high prevalence of stunting and wasting persist alongside a disproportionate increase in the prevalence of overweight in these groups. Conclusions The observed pattern in stunting (high and persistent prevalence) and increase in overweight elucidate setbacks in advances already observed in previous periods and stresses the need for social and political strategies to address multiple forms of malnutrition.

The COVID-19 pandemic has challenged researchers and policy makers to identify public safety measures forpreventing the collapse of healthcare systems and reducingdeaths. This narrative review summarizes the available evidence on the impact of social distancing measures on the epidemic and discusses the implementation of these measures in Brazil. Articles on the effect of social distancing on COVID-19 were selected from the PubMed, medRXiv and bioRvix databases. Federal and state legislation was analyzed to summarize the strategies implemented in Brazil. Social distancing measures adopted by the population appear effective, particularly when implemented in conjunction with the isolation of cases and quarantining of contacts. Therefore, social distancing measures, and social protection policies to guarantee the sustainability of these measures, should be implemented. To control COVID-19 in Brazil, it is also crucial that epidemiological monitoring is strengthened at all three levels of the Brazilian National Health System (SUS). This includes evaluating and usingsupplementary indicators to monitor the progression of the pandemic and the effect of the control measures, increasing testing capacity, and making disaggregated notificationsand testing resultstransparentand broadly available.