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2.
Cien Saude Colet ; 25(9): 3567-3571, 2020 Sep.
Artigo em Inglês, Português | MEDLINE | ID: mdl-32876259

RESUMO

On February 3, 2020, the Brazilian Ministry of Health declared a state of emergency in public health of national relevance due to the pandemic caused by the new coronavirus SARS-CoV-2. As a result, IBGE postponed the 2020 Demographic Census and started to formulate a COVID-19 PNAD. The survey included a total sample of 349 thousand people in about 200 thousand households. Of the total Brazilian resident population, the IBGE estimated in May/2020 that 24.0 million (11.4%) had at least one of the flu-like syndrome symptoms. Of this contingent, 20.2 million (84.3% of all symptomatic patients) did not seek health care. The innovations brought to health surveillance and the IBGE's pioneering spirit show that it is possible, in a continental country that has been experiencing several local epidemics at different times in its territory, that other countries also develop similar household surveys, with weekly data collection (referred to epidemiological weeks) by telephone in an innovative and timely manner. The COVID-19 PNAD also brought new technology to the Institute, reviving its role as an external evaluator of the Unified Health System (SUS).


Assuntos
Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Vigilância em Saúde Pública/métodos , Saúde Pública , Inquéritos e Questionários , Betacoronavirus/isolamento & purificação , Tecnologia Biomédica , Brasil , Infecções por Coronavirus/terapia , Infecções por Coronavirus/virologia , Assistência à Saúde/organização & administração , Humanos , Pandemias , Aceitação pelo Paciente de Cuidados de Saúde/estatística & dados numéricos , Pneumonia Viral/terapia , Pneumonia Viral/virologia
3.
J Med Internet Res ; 22(9): e20924, 2020 09 22.
Artigo em Inglês | MEDLINE | ID: mdl-32915762

RESUMO

BACKGROUND: SARS-CoV-2, the novel coronavirus that causes COVID-19, is a global pandemic with higher mortality and morbidity than any other virus in the last 100 years. Without public health surveillance, policy makers cannot know where and how the disease is accelerating, decelerating, and shifting. Unfortunately, existing models of COVID-19 contagion rely on parameters such as the basic reproduction number and use static statistical methods that do not capture all the relevant dynamics needed for surveillance. Existing surveillance methods use data that are subject to significant measurement error and other contaminants. OBJECTIVE: The aim of this study is to provide a proof of concept of the creation of surveillance metrics that correct for measurement error and data contamination to determine when it is safe to ease pandemic restrictions. We applied state-of-the-art statistical modeling to existing internet data to derive the best available estimates of the state-level dynamics of COVID-19 infection in the United States. METHODS: Dynamic panel data (DPD) models were estimated with the Arellano-Bond estimator using the generalized method of moments. This statistical technique enables control of various deficiencies in a data set. The validity of the model and statistical technique was tested. RESULTS: A Wald chi-square test of the explanatory power of the statistical approach indicated that it is valid (χ210=1489.84, P<.001), and a Sargan chi-square test indicated that the model identification is valid (χ2946=935.52, P=.59). The 7-day persistence rate for the week of June 27 to July 3 was 0.5188 (P<.001), meaning that every 10,000 new cases in the prior week were associated with 5188 cases 7 days later. For the week of July 4 to 10, the 7-day persistence rate increased by 0.2691 (P=.003), indicating that every 10,000 new cases in the prior week were associated with 7879 new cases 7 days later. Applied to the reported number of cases, these results indicate an increase of almost 100 additional new cases per day per state for the week of July 4-10. This signifies an increase in the reproduction parameter in the contagion models and corroborates the hypothesis that economic reopening without applying best public health practices is associated with a resurgence of the pandemic. CONCLUSIONS: DPD models successfully correct for measurement error and data contamination and are useful to derive surveillance metrics. The opening of America involves two certainties: the country will be COVID-19-free only when there is an effective vaccine, and the "social" end of the pandemic will occur before the "medical" end. Therefore, improved surveillance metrics are needed to inform leaders of how to open sections of the United States more safely. DPD models can inform this reopening in combination with the extraction of COVID-19 data from existing websites.


Assuntos
Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Política de Saúde , Modelos Biológicos , Modelos Estatísticos , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Vigilância em Saúde Pública/métodos , Betacoronavirus , Infecções por Coronavirus/prevenção & controle , Humanos , Pandemias/prevenção & controle , Pandemias/estatística & dados numéricos , Pneumonia Viral/prevenção & controle , Reprodutibilidade dos Testes , Estados Unidos/epidemiologia
4.
PLoS Comput Biol ; 16(9): e1007836, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32960900

RESUMO

Early warning signals (EWS) identify systems approaching a critical transition, where the system undergoes a sudden change in state. For example, monitoring changes in variance or autocorrelation offers a computationally inexpensive method which can be used in real-time to assess when an infectious disease transitions to elimination. EWS have a promising potential to not only be used to monitor infectious diseases, but also to inform control policies to aid disease elimination. Previously, potential EWS have been identified for prevalence data, however the prevalence of a disease is often not known directly. In this work we identify EWS for incidence data, the standard data type collected by the Centers for Disease Control and Prevention (CDC) or World Health Organization (WHO). We show, through several examples, that EWS calculated on simulated incidence time series data exhibit vastly different behaviours to those previously studied on prevalence data. In particular, the variance displays a decreasing trend on the approach to disease elimination, contrary to that expected from critical slowing down theory; this could lead to unreliable indicators of elimination when calculated on real-world data. We derive analytical predictions which can be generalised for many epidemiological systems, and we support our theory with simulated studies of disease incidence. Additionally, we explore EWS calculated on the rate of incidence over time, a property which can be extracted directly from incidence data. We find that although incidence might not exhibit typical critical slowing down properties before a critical transition, the rate of incidence does, presenting a promising new data type for the application of statistical indicators.


Assuntos
Doenças Transmissíveis/epidemiologia , Biologia Computacional/métodos , Modelos Estatísticos , Vigilância em Saúde Pública/métodos , Controle de Doenças Transmissíveis , Humanos , Incidência , Prevalência
5.
Rev Soc Bras Med Trop ; 53: e20200528, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32935787

RESUMO

INTRODUCTION: The coronavirus disease (COVD-19) outbreak has overburdened the surveillance of severe acute respiratory infections (SARIs), including the laboratory network. This study was aimed at correcting the absence of laboratory results of reported SARI deaths. METHODS: The imputation method was applied for SARI deaths without laboratory information using clinico-epidemiological characteristics. RESULTS: Of 84,449 SARI deaths, 51% were confirmed with COVID-19 while 3% with other viral respiratory diseases. After the imputation method, 95% of deaths were reclassified as COVID-19 while 5% as other viral respiratory diseases. CONCLUSIONS: The imputation method was a useful and robust solution (sensitivity and positive predictive value of 98%) for missing values through clinical & epidemiological characteristics.


Assuntos
Infecções por Coronavirus/epidemiologia , Surtos de Doenças , Pneumonia Viral/epidemiologia , Vigilância em Saúde Pública/métodos , Algoritmos , Brasil/epidemiologia , Humanos , Pandemias
7.
JMIR Public Health Surveill ; 6(3): e19399, 2020 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-32788148

RESUMO

BACKGROUND: Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the number of cases of coronavirus disease (COVID-19) in the United States has exponentially increased. Identifying and monitoring individuals with COVID-19 and individuals who have been exposed to the disease is critical to prevent transmission. Traditional contact tracing mechanisms are not structured on the scale needed to address this pandemic. As businesses reopen, institutions and agencies not traditionally engaged in disease prevention are being tasked with ensuring public safety. Systems to support organizations facing these new challenges are critically needed. Most currently available symptom trackers use a direct-to-consumer approach and use personal identifiers, which raises privacy concerns. OBJECTIVE: Our aim was to develop a monitoring and reporting system for COVID-19 to support institutions conducting monitoring activities without compromising privacy. METHODS: Our multidisciplinary team designed a symptom tracking system after consultation with experts. The system was designed in the Georgetown University AvesTerra knowledge management environment, which supports data integration and synthesis to identify actionable events and maintain privacy. We conducted a beta test for functionality among consenting Georgetown University medical students. RESULTS: The symptom tracker system was designed based on guiding principles developed during peer consultations. Institutions are provided access to the system through an efficient onboarding process that uses clickwrap technology to document agreement to limited terms of use to rapidly enable free access. Institutions provide their constituents with a unique identifier to enter data through a web-based user interface to collect vetted symptoms as well as clinical and epidemiologic data. The website also provides individuals with educational information through links to the COVID-19 prevention recommendations from the US Centers for Disease Control and Prevention. Safety features include instructions for people with new or worsening symptoms to seek care. No personal identifiers are collected in the system. The reporter mechanism safeguards data access so that institutions can only access their own data, and it provides institutions with on-demand access to the data entered by their constituents, organized in summary reports that highlight actionable data. Development of the system began on March 15, 2020, and it was launched on March 20, 2020. In the beta test, 48 Georgetown University School of Medicine students or their social contacts entered data into the system from March 31 to April 5, 2020. One of the 48 users (2%) reported active COVID-19 infection and had no symptoms by the end of the monitoring period. No other participants reported symptoms. Only data with the unique entity identifier for our beta test were generated in our summary reports. CONCLUSIONS: This system harnesses insights into privacy and data sharing to avoid regulatory and legal hurdles to rapid adaption by entities tasked with maintaining public safety. Our pilot study demonstrated feasibility and ease of use. Refinements based on feedback from early adapters included release of a Spanish language version. These systems provide technological advances to complement the traditional contact tracing and digital tracing applications being implemented to limit SARS-CoV-2 transmission during reopening.


Assuntos
Comércio/organização & administração , Infecções por Coronavirus/prevenção & controle , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Vigilância em Saúde Pública/métodos , Segurança , Busca de Comunicante/economia , Infecções por Coronavirus/epidemiologia , Estudos de Viabilidade , Humanos , Projetos Piloto , Pneumonia Viral/epidemiologia , Privacidade , Avaliação de Sintomas , Estados Unidos/epidemiologia
8.
PLoS Comput Biol ; 16(8): e1008117, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32804932

RESUMO

Understanding the behavior of emerging disease outbreaks in, or ahead of, real-time could help healthcare officials better design interventions to mitigate impacts on affected populations. Most healthcare-based disease surveillance systems, however, have significant inherent reporting delays due to data collection, aggregation, and distribution processes. Recent work has shown that machine learning methods leveraging a combination of traditionally collected epidemiological information and novel Internet-based data sources, such as disease-related Internet search activity, can produce meaningful "nowcasts" of disease incidence ahead of healthcare-based estimates, with most successful case studies focusing on endemic and seasonal diseases such as influenza and dengue. Here, we apply similar computational methods to emerging outbreaks in geographic regions where no historical presence of the disease of interest has been observed. By combining limited available historical epidemiological data available with disease-related Internet search activity, we retrospectively estimate disease activity in five recent outbreaks weeks ahead of traditional surveillance methods. We find that the proposed computational methods frequently provide useful real-time incidence estimates that can help fill temporal data gaps resulting from surveillance reporting delays. However, the proposed methods are limited by issues of sample bias and skew in search query volumes, perhaps as a result of media coverage.


Assuntos
Surtos de Doenças/estatística & dados numéricos , Internet , Vigilância em Saúde Pública/métodos , Ferramenta de Busca/estatística & dados numéricos , Biologia Computacional , Coleta de Dados/métodos , Métodos Epidemiológicos , Humanos , Aprendizado de Máquina
9.
PLoS Negl Trop Dis ; 14(8): e0008545, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32841252

RESUMO

The analysis of zoonotic disease risk requires the consideration of both human and animal geo-referenced disease incidence data. Here we show an application of joint Bayesian analyses to the study of echinococcosis granulosus (EG) in the province of Rio Negro, Argentina. We focus on merging passive and active surveillance data sources of animal and human EG cases using joint Bayesian spatial and spatio-temporal models. While similar spatial clustering and temporal trending was apparent, there appears to be limited lagged dependence between animal and human outcomes. Beyond the data quality issues relating to missingness at different times, we were able to identify relations between dog and human data and the highest 'at risk' areas for echinococcosis within the province.


Assuntos
Doenças do Cão/epidemiologia , Equinococose/epidemiologia , Vigilância em Saúde Pública/métodos , Zoonoses/epidemiologia , Adolescente , Animais , Argentina/epidemiologia , Teorema de Bayes , Criança , Cães , Echinococcus granulosus , Humanos , Modelos Biológicos
10.
Public Health Rep ; 135(1_suppl): 182S-188S, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32735204

RESUMO

OBJECTIVES: We evaluated the impact of a 2014 New York City health code change requiring laboratories to indicate if a patient is pregnant or probably pregnant in the electronic laboratory report (ELR) when reporting syphilis and hepatitis B virus (HBV) cases to the New York City Department of Health and Mental Hygiene (DOHMH). METHODS: We calculated the number of pregnant persons with syphilis or HBV infection reported to DOHMH from January 1, 2013, through June 30, 2018. We compared the proportion in which the first report to DOHMH was an ELR with pregnancy indicated before and after the policy change. We calculated time between first ELR with pregnancy indicated and subsequent reporting by a method other than ELR and the proportion of cases in which ELR with pregnancy indicated was the only report source. RESULTS: A total of 552 new syphilis and 8414 HBV-infected cases were reported to DOHMH. From January 2013-June 2014 (pre-change) to January 2017-June 2018 (post-change), the proportion of cases in which ELR with pregnancy indicated was the first report to DOHMH increased significantly (14.7% [23/156] to 46.2% [80/173] for syphilis; 8.0% [200/2498] to 45.3% [851/1879] for HBV infection [P < .001]). Median time between first ELR with pregnancy indicated and subsequent reporting by a method other than ELR was 9.0 days for syphilis and 51.0 days for HBV infection. ELR with pregnancy indicated was the only report for 43.1% (238/552) of syphilis cases and 23.4% (1452/6200) of HBV cases during the study period. CONCLUSION: Including pregnancy status with ELR can increase the ability of public health departments to conduct timely interventions to prevent mother-to-child transmission.


Assuntos
Hepatite B/diagnóstico , Complicações Infecciosas na Gravidez/diagnóstico , Vigilância em Saúde Pública/métodos , Sífilis/diagnóstico , Adolescente , Adulto , Feminino , Humanos , Transmissão Vertical de Doença Infecciosa/prevenção & controle , Cidade de Nova Iorque , Gravidez , Complicações Infecciosas na Gravidez/prevenção & controle , Adulto Jovem
11.
Public Health Rep ; 135(1_suppl): 75S-81S, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32735184

RESUMO

Policies facilitating integration of public health programs can improve the public health response, but the literature on approaches to integration across multiple system levels is limited. We describe the efforts of the Massachusetts Department of Public Health to integrate its HIV, viral hepatitis, sexually transmitted infection (STI), and tuberculosis response through policies that mandated contracted organizations to submit specimens for testing to the Massachusetts State Public Health Laboratory; co-test blood specimens for HIV, hepatitis C virus (HCV), and syphilis; integrate HIV, viral hepatitis, and STI disease surveillance and case management in a single data system; and implement an integrated infectious disease drug assistance program. From 2014 through 2018, the number of tests performed by the Massachusetts State Public Health Laboratory increased from 16 321 to 33 674 for HIV, from 11 054 to 33 670 for HCV, and from 19 169 to 30 830 for syphilis. Service contracts enabled rapid response to outbreaks of HIV, hepatitis A, and hepatitis B. Key challenges included lack of a billing infrastructure at the Massachusetts State Public Health Laboratory; the need to complete negotiations with insurers and to establish a retained revenue account to receive health insurance reimbursements for testing services; and time to train testing providers in phlebotomy for required testing. Investing in laboratory infrastructure; creating billing mechanisms to maximize health insurance reimbursement; proactively engaging providers, community members, and other stakeholders; and building capacity to transform practices are needed. Using multilevel policy approaches to integrate the public health response to HIV, STI, viral hepatitis, and tuberculosis is feasible and adaptable to other public health programs.


Assuntos
Serviços Contratados/organização & administração , Seguro Saúde/organização & administração , Administração em Saúde Pública/métodos , Vigilância em Saúde Pública/métodos , Doenças Sexualmente Transmissíveis/diagnóstico , Serviços Contratados/economia , Serviços Contratados/normas , Política de Saúde , Acesso aos Serviços de Saúde , Hepatite/diagnóstico , Humanos , Seguro Saúde/economia , Seguro Saúde/legislação & jurisprudência , Seguro Saúde/normas , Reembolso de Seguro de Saúde/economia , Reembolso de Seguro de Saúde/legislação & jurisprudência , Reembolso de Seguro de Saúde/normas , Relações Interinstitucionais , Massachusetts , Estudos de Casos Organizacionais , Avaliação de Programas e Projetos de Saúde , Administração em Saúde Pública/economia , Administração em Saúde Pública/legislação & jurisprudência , Administração em Saúde Pública/normas , Sífilis/diagnóstico
13.
Public Health Rep ; 135(5): 621-630, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32791022

RESUMO

OBJECTIVE: Electronic health records (EHRs) hold promise as a public health surveillance tool, but questions remain about how EHR patients compare with populations in health and demographic surveys. We compared population characteristics from a regional distributed data network (DDN), which securely and confidentially aggregates EHR data from multiple health care organizations in the same geographic region, with population characteristics from health and demographic surveys. METHODS: Ten health care organizations participating in a Colorado DDN contributed data for coverage estimation. We aggregated demographic and geographic data from 2017 for patients aged ≥18 residing in 7 counties. We used a cross-sectional design to compare DDN population size, by county, with the following survey-estimated populations: the county population, estimated by the American Community Survey (ACS); residents seeking any health care, estimated by the Colorado Health Access Survey; and residents seeking routine (eg, primary) health care, estimated by the Behavioral Risk Factor Surveillance System. We also compared data on the DDN and survey populations by sex, age group, race/ethnicity, and poverty level to assess surveillance system representativeness. RESULTS: The DDN population included 609 840 people in 7 counties, corresponding to 25% coverage of the general adult population. Population coverage ranged from 15% to 35% across counties. Demographic distributions generated by DDN and surveys were similar for many groups. Overall, the DDN and surveys assessing care-seeking populations had a higher proportion of women and older adults than the ACS population. The DDN included higher proportions of Hispanic people and people living in high-poverty neighborhoods compared with the surveys. CONCLUSION: The DDN population is not a random sample of the regional adult population; it is influenced by health care use patterns and organizations participating in the DDN. Strengths and limitations of DDNs complement those of survey-based approaches. The regional DDN is a promising public health surveillance tool.


Assuntos
Registros Eletrônicos de Saúde/estatística & dados numéricos , Geografia , Acesso aos Serviços de Saúde/estatística & dados numéricos , Aceitação pelo Paciente de Cuidados de Saúde/estatística & dados numéricos , Vigilância em Saúde Pública/métodos , Fatores Socioeconômicos , Adulto , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Colorado , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Fatores Sexuais , Inquéritos e Questionários , Adulto Jovem
14.
Arq. ciências saúde UNIPAR ; 24(2): 125-129, maio-ago. 2020.
Artigo em Português | LILACS | ID: biblio-1116382

RESUMO

As Diretrizes Curriculares Nacionais para a graduação em Medicina no Brasil destacam que os profissionais de saúde devem estar aptos para realizar ações de promoção, prevenção, reabilitação e proteção em saúde, nas quais a Vigilância em Saúde desempenha papel fundamental. Nesse contexto, este relato de experiência aborda uma estratégia ativa de ensino que visa, por meio de um júri simulado, aplicar conceitos de Vigilância em Saúde (Epidemiológica, Sanitária e Ambiental); fomentar a discussão técnica sobre sua atuação; e discutir vigilância, risco e mitigação do risco em situações de desastres. A atividade foi realizada dentro da disciplina de Saúde Coletiva com participação de 60 discentes do quinto período do curso de medicina e 2 docentes, duração de 4 horas e teve como situação problema o rompimento da barragem do município de Mariana em 2015 e os danos à saúde da população dessa área. Para melhor organização do júri simulado e para assegurar a participação ativa do maior número de discentes nas discussões, os alunos foram divididos nas seguintes funções: júri popular, escrivães, acusação, defesa, testemunhas e peritos. Além disso, as arguições deveriam ser respaldas por literatura científica e aplicar os conceitos epidemiológicos, sanitários e ambientais na situação proposta. Assim, este júri simulado busca aprimorar o processo de ensino-aprendizagem em Vigilância em Saúde por meio de uma atividade prática sobre sua atuação, que ressalte a participação do médico nessa esfera da saúde pública.


The National Curricular Guidelines for medical graduation in Brazil emphasizes that physicians should be able to develop health promotion, prevention, rehabilitation, and protective actions in which Health Surveillance plays a pivotal role. Thereby, this experience report addresses an active teaching strategy that aims, through a simulated jury, at applying the concepts of Health Surveillance (Epidemiological, Sanitary, and Environmental); promoting the technical discussion about its roles; and discussing health surveillance, risk, and risk mitigation in disaster situations. The activity is part of the Public Health discipline, and it was developed with 60 medical students from the fifth period and 2 teachers. The jury lasted 4 hours and the topic was the rupture of a tailing dam in the city of Mariana in 2015, addressing the damages to the health of the population. For better organization of the simulated jury and to ensure the participation of the largest number of students, they were divided into the following roles: popular jury, clerks, prosecution, defense, witnesses, and criminal investigators. In addition, the arguments should be supported by scientific literature and should also apply epidemiological, health and environmental concepts. Thus, this simulated jury sought to improve the teaching-learning process in Health Surveillance with a practical activity about its duties and highlight the importance and the role of physicians in this public health area.


Assuntos
Humanos , Masculino , Feminino , Aprendizagem Baseada em Problemas/métodos , Desastres/estatística & dados numéricos , Educação Médica/métodos , Colapso Estrutural/prevenção & controle , Vigilância em Saúde Pública/métodos , Treinamento por Simulação/legislação & jurisprudência , Estudantes de Medicina/classificação , Ensino/educação , Vigilância Sanitária/normas , Brasil/epidemiologia , Monitoramento Ambiental/métodos , Cidades/epidemiologia , Poluição Ambiental/análise , Saúde da População/história , Aprendizagem/ética
15.
MMWR Morb Mortal Wkly Rep ; 69(26): 815-819, 2020 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-32614808

RESUMO

In May 2019, the New York City Department of Health and Mental Hygiene (NYCDOHMH) detected an unusual cluster of five salmonellosis patients via automated spatiotemporal analysis of notifiable diseases using free SaTScan software (1). Within 1 day of cluster detection, graduate student interviewers determined that three of the patients had eaten prepared food from the same grocery store (establishment A) located inside the cluster area. NYCDOHMH initiated an investigation to identify additional cases, establish the cause, and provide control recommendations. Overall, 15 New York City (NYC) residents with laboratory-diagnosed salmonellosis who reported eating food from establishment A were identified. The most commonly consumed food item was chicken, reported by 10 patients. All 11 clinical isolates available were serotyped as Salmonella Blockley, sequenced, and analyzed by core genome multilocus sequence typing; isolates had a median difference of zero alleles. Environmental assessments revealed food not held at the proper temperature, food not cooled properly, and potential cross-contamination during chicken preparation. Elevated fecal coliform counts were found in two of four ready-to-eat food samples collected from establishment A, and Bacillus cereus was detected in three. The outbreak strain of Salmonella was isolated from one patient's leftover chicken. Establishing automated spatiotemporal cluster detection analyses for salmonellosis and other reportable diseases could aid in the detection of geographically focused, community-acquired outbreaks even before laboratory subtyping results become available.


Assuntos
Surtos de Doenças , Vigilância em Saúde Pública/métodos , Intoxicação Alimentar por Salmonella/epidemiologia , Análise Espaço-Temporal , Adulto , Automação , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Cidade de Nova Iorque/epidemiologia , Salmonella/genética , Salmonella/isolamento & purificação , Intoxicação Alimentar por Salmonella/diagnóstico , Sorogrupo
16.
Cad Saude Publica ; 36(7): e00120020, 2020.
Artigo em Inglês, Português | MEDLINE | ID: mdl-32638881

RESUMO

Manaus, the capital of the Brazilian State of Amazonas, is the current epicenter of the COVID-19 epidemic in Amazonia. The sharp increase in deaths is a huge concern for health system administrators and society. The study aimed to analyze excess overall mortality according to Epidemiological Week (EW) in order to identify changes potentially associated with the epidemic in Manaus. Overall and cause-specific mortality data were obtained from the Central Database of the National Civil Registry and the Mortality Information System for 2018, 2019, and 2020. The study analyzed age bracket, sex, place of death, EW, calendar year, and causes of death. Ratios were calculated between deaths in 2019/2018 and 2020/2019 to estimate excess deaths, with 5% confidence intervals. No significant excess overall mortality was seen in the ratios for 2019/2018, independently of EW. Meanwhile, the ratios for 2020/2019 increased from 1.0 (95%CI: 0.9-1.3) in EW 11 to 4.6 (95%CI: 3.9-5.3) in EW 17. Excess overall mortality was observed with increasing age, especially in individuals 60 years or older, who accounted for 69.1% (95%CI: 66.8-71.4) of the deaths. The ratios for 2020/2019 for deaths at home or on public byways were 1.1 (95%CI: 0.7-1.8) in EW 12 and 7.8 (95%CI: 5.4-11.2) in EW 17. The explosion in overall mortality in Manaus and the high proportion of deaths at home or on public byways reveals the epidemic's severity in contexts of heavy social inequality and weak effectiveness of government policies, especially policies meant to deal with social inequalities and strengthen the Unified Health System.


Assuntos
Infecções por Coronavirus/epidemiologia , Mortalidade/tendências , Pneumonia Viral/epidemiologia , Vigilância em Saúde Pública/métodos , Adolescente , Adulto , Distribuição por Idade , Idoso , Idoso de 80 Anos ou mais , Betacoronavirus , Brasil/epidemiologia , Causas de Morte , Criança , Pré-Escolar , Infecções por Coronavirus/mortalidade , Estudos Transversais , Humanos , Lactente , Recém-Nascido , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/mortalidade , Distribuição por Sexo , Populações Vulneráveis , Adulto Jovem
17.
JMIR Public Health Surveill ; 6(3): e22331, 2020 07 31.
Artigo em Inglês | MEDLINE | ID: mdl-32678799

RESUMO

Epidemiologic and syndromic surveillance metrics traditionally used by public health departments can be enhanced to better predict hospitalization for coronavirus disease (COVID-19). In Montgomery County, Maryland, measurements of oxygen saturation (SpO2) by pulse oximetry obtained by the emergency medical service (EMS) were added to these traditional metrics to enhance the public health picture for decision makers. During a 78-day period, the rolling 7-day average of the percentage of EMS patients with SpO2 <94% had a stronger correlation with next-day hospital bed occupancy (Spearman ρ=0.58, 95% CI 0.40-0.71) than either the rolling 7-day average of the percentage of positive tests (ρ=0.55, 95% CI: 0.37-0.69) or the rolling 7-day average of the percentage of emergency department visits for COVID-19-like illness (ρ=0.49, 95% CI: 0.30-0.64). Health departments should consider adding EMS data to augment COVID-19 surveillance and thus improve resource allocation.


Assuntos
Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/terapia , Serviços Médicos de Emergência/estatística & dados numéricos , Pneumonia Viral/epidemiologia , Pneumonia Viral/terapia , Vigilância em Saúde Pública/métodos , Humanos , Maryland/epidemiologia , Pandemias
18.
Epidemiol Infect ; 148: e122, 2020 06 18.
Artigo em Inglês | MEDLINE | ID: mdl-32614283

RESUMO

The COVID-19 pandemic is exerting major pressures on society, health and social care services and science. Understanding the progression and current impact of the pandemic is fundamental to planning, management and mitigation of future impact on the population. Surveillance is the core function of any public health system, and a multi-component surveillance system for COVID-19 is essential to understand the burden across the different strata of any health system and the population. Many countries and public health bodies utilise 'syndromic surveillance' (using real-time, often non-specific symptom/preliminary diagnosis information collected during routine healthcare provision) to supplement public health surveillance programmes. The current COVID-19 pandemic has revealed a series of unprecedented challenges to syndromic surveillance including: the impact of media reporting during early stages of the pandemic; changes in healthcare-seeking behaviour resulting from government guidance on social distancing and accessing healthcare services; and changes in clinical coding and patient management systems. These have impacted on the presentation of syndromic outputs, with changes in denominators creating challenges for the interpretation of surveillance data. Monitoring changes in healthcare utilisation is key to interpreting COVID-19 surveillance data, which can then be used to better understand the impact of the pandemic on the population. Syndromic surveillance systems have had to adapt to encompass these changes, whilst also innovating by taking opportunities to work with data providers to establish new data feeds and develop new COVID-19 indicators. These developments are supporting the current public health response to COVID-19, and will also be instrumental in the continued and future fight against the disease.


Assuntos
Infecções por Coronavirus/epidemiologia , Pandemias/estatística & dados numéricos , Pneumonia Viral/epidemiologia , Vigilância da População/métodos , Infecções por Coronavirus/prevenção & controle , Comportamentos Relacionados com a Saúde , Humanos , Pandemias/prevenção & controle , Aceitação pelo Paciente de Cuidados de Saúde/estatística & dados numéricos , Pneumonia Viral/prevenção & controle , Vigilância em Saúde Pública/métodos
19.
JMIR Public Health Surveill ; 6(3): e19354, 2020 07 17.
Artigo em Inglês | MEDLINE | ID: mdl-32640418

RESUMO

BACKGROUND: Coronavirus disease (COVID-19) is a novel viral illness that has rapidly spread worldwide. While the disease primarily presents as a respiratory illness, gastrointestinal symptoms such as diarrhea have been reported in up to one-third of confirmed cases, and patients may have mild symptoms that do not prompt them to seek medical attention. Internet-based infodemiology offers an approach to studying symptoms at a population level, even in individuals who do not seek medical care. OBJECTIVE: This study aimed to determine if a correlation exists between internet searches for gastrointestinal symptoms and the confirmed case count of COVID-19 in the United States. METHODS: The search terms chosen for analysis in this study included common gastrointestinal symptoms such as diarrhea, nausea, vomiting, and abdominal pain. Furthermore, the search terms fever and cough were used as positive controls, and constipation was used as a negative control. Daily query shares for the selected symptoms were obtained from Google Trends between October 1, 2019 and June 15, 2020 for all US states. These shares were divided into two time periods: pre-COVID-19 (prior to March 1) and post-COVID-19 (March 1-June 15). Confirmed COVID-19 case numbers were obtained from the Johns Hopkins University Center for Systems Science and Engineering data repository. Moving averages of the daily query shares (normalized to baseline pre-COVID-19) were then analyzed against the confirmed disease case count and daily new cases to establish a temporal relationship. RESULTS: The relative search query shares of many symptoms, including nausea, vomiting, abdominal pain, and constipation, remained near or below baseline throughout the time period studied; however, there were notable increases in searches for the positive control symptoms of fever and cough as well as for diarrhea. These increases in daily search queries for fever, cough, and diarrhea preceded the rapid rise in number of cases by approximately 10 to 14 days. The search volumes for these terms began declining after mid-March despite the continued rises in cumulative cases and daily new case counts. CONCLUSIONS: Google searches for symptoms may precede the actual rises in cases and hospitalizations during pandemics. During the current COVID-19 pandemic, this study demonstrates that internet search queries for fever, cough, and diarrhea increased prior to the increased confirmed case count by available testing during the early weeks of the pandemic in the United States. While the search volumes eventually decreased significantly as the number of cases continued to rise, internet query search data may still be a useful tool at a population level to identify areas of active disease transmission at the cusp of new outbreaks.


Assuntos
Infecções por Coronavirus/diagnóstico , Gastroenteropatias/epidemiologia , Pandemias , Pneumonia Viral/diagnóstico , Vigilância em Saúde Pública/métodos , Ferramenta de Busca/estatística & dados numéricos , Infecções por Coronavirus/epidemiologia , Humanos , Pneumonia Viral/epidemiologia , Estados Unidos/epidemiologia
20.
MMWR Morb Mortal Wkly Rep ; 69(29): 960-964, 2020 Jul 24.
Artigo em Inglês | MEDLINE | ID: mdl-32701938

RESUMO

Population prevalence of persons infected with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), varies by subpopulation and locality. U.S. studies of SARS-CoV-2 infection have examined infections in nonrandom samples (1) or seroprevalence in specific populations* (2), which are limited in their generalizability and cannot be used to accurately calculate infection-fatality rates. During April 25-29, 2020, Indiana conducted statewide random sample testing of persons aged ≥12 years to assess prevalence of active infection and presence of antibodies to SARS-CoV-2; additional nonrandom sampling was conducted in racial and ethnic minority communities to better understand the impact of the virus in certain racial and ethnic minority populations. Estimates were adjusted for nonresponse to reflect state demographics using an iterative proportional fitting method. Among 3,658 noninstitutionalized participants in the random sample survey, the estimated statewide point prevalence of active SARS-CoV-2 infection confirmed by reverse transcription-polymerase chain reaction (RT-PCR) testing was 1.74% (95% confidence interval [CI] = 1.10-2.54); 44.2% of these persons reported no symptoms during the 2 weeks before testing. The prevalence of immunoglobulin G (IgG) seropositivity, indicating past infection, was 1.09% (95% CI = 0.76-1.45). The overall prevalence of current and previous infections of SARS-CoV-2 in Indiana was 2.79% (95% CI = 2.02-3.70). In the random sample, higher overall prevalences were observed among Hispanics and those who reported having a household contact who had previously been told by a health care provider that they had COVID-19. By late April, an estimated 187,802 Indiana residents were currently or previously infected with SARS-CoV-2 (9.6 times higher than the number of confirmed cases [17,792]) (3), and 1,099 residents died (infection-fatality ratio = 0.58%). The number of reported cases represents only a fraction of the estimated total number of infections. Given the large number of persons who remain susceptible in Indiana, adherence to evidence-based public health mitigation and containment measures (e.g., social distancing, consistent and correct use of face coverings, and hand hygiene) is needed to reduce surge in hospitalizations and prevent morbidity and mortality from COVID-19.


Assuntos
Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Vigilância em Saúde Pública/métodos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Grupos de Populações Continentais/estatística & dados numéricos , Infecções por Coronavirus/etnologia , Grupos Étnicos/estatística & dados numéricos , Feminino , Humanos , Indiana/epidemiologia , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/etnologia , Prevalência , Adulto Jovem
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