A Vulnerability Analysis for the Management of and Response to the COVID-19 Epidemic in the Second Most Populous State in Brazil

The COVID-19 pandemic has the potential to affect all individuals, however in a heterogeneous way. In this sense, identifying specificities of each location is essential to minimize the damage caused by the disease. Therefore, the aim of this research was to assess the vulnerability of 853 municipalities in the second most populous state in Brazil, Minas Gerais (MG), in order to direct public policies. An epidemiological study was carried out based on Multi-Criteria Decision Analysis (MCDA) using indicators with some relation to the process of illness and death caused by COVID-19. The indicators were selected by a literature search and categorized into: demographic, social, economic, health infrastructure, population at risk and epidemiological. The variables were collected in Brazilian government databases at the municipal level and evaluated according to MCDA, through the Program to Support Decision Making based on Indicators (PRADIN). Based on this approach, the study performed simulations by category of indicators and a general simulation that allowed to divide the municipalities into groups of 1–5, with 1 being the least vulnerable and 5 being the most vulnerable. The groupings of municipalities were exposed in their respective mesoregions of MG in a thematic map, using the software Tabwin 32. The results revealed that the mesoregion of Norte de Minas stands out with more than 40% of its municipalities belonging to group 5, according to economic, social and health infrastructure indicators. Similarly, the Jequitinhonha mesoregion exhibited almost 60% of the municipalities in this group for economic and health infrastructure indicators. For demographic and epidemiological criteria, the Metropolitana de Belo Horizonte was the most vulnerable mesoregion, with 42.9 and 26.7% of the municipalities in group 5, respectively. Considering the presence of a population at risk, Zona da Mata reported 42.3% of the municipalities in the most vulnerable group. In the joint analysis of data, the Jequitinhonha, Vale do Mucuri and Vale do Rio Doce mesoregions were the most vulnerable in the state of MG. Thus, through the outlined profile, the present study proved how socioeconomic diversity affects the vulnerability of the municipalities to face COVID-19 outbreak, highlighting the need for interventions directed to each reality.

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A vulnerability analysis for the management of and response to the COVID-19 epidemic in the second most populous state in Brazil

10.1101/2020.07.20.20158345 ◽

2020 ◽

Author(s):

Igor Silva Campos ◽

Vinicius Ferreira Aratani ◽

Karina Baltor Cabral ◽

Jean Ezequiel Limongi ◽

Stefan Vilges de Oliveira

Keyword(s):

At Risk ◽

Joint Analysis ◽

Population At Risk ◽

Brazilian Government ◽

Health Infrastructure ◽

Socioeconomic Diversity ◽

Group 5 ◽

Belo Horizonte ◽

Municipal Level ◽

Support Decision Making

The COVID-19 pandemic has the potential to affect all individuals, however in a heterogeneous way. In this sense, identifying specificities of each location is essential to minimize the damage caused by the disease. Therefore, the aim of this research was to assess the vulnerability of the 853 municipalities in the second most populous state in Brazil, Minas Gerais (MG), in order to direct public policies. Then, an epidemiological study was carried out based on Multi-Criteria Decision Analysis (MCDA) using indicators with some relation to the process of illness and death caused by COVID-19. The indicators were selected by a literature review and categorized into: demographic, social, economic, health infrastructure, population at risk and epidemiological. The variables were collected in Brazilian government databases at the municipal level and evaluated according to MCDA, through the Program to Support Decision Making based on indicators (PRADIN). Based on this approach, the study performed simulations by category of indicators and a general simulation that allowed to divide the municipalities into groups of 1 to 5, with 1 being the least vulnerable and 5 being the most vulnerable. The groupings of municipalities were exposed in their respective mesoregions of MG in a thematic map, using the software Tabwin 32. The results revealed that the mesoregion of Norte de Minas stands out with more than 40% of its municipalities belonging to group 5, according to economic, social and health infrastructure indicators. Similarly, the Jequitinhonha mesoregion exhibited almost 60% of the municipalities in this group for economic and health infrastructure indicators. For demographic and epidemiological criteria, the Metropolitana de Belo Horizonte mesoregion is the most vulnerable, with 42.9% and 26.7% of the municipalities in group 5, respectively. Considering the presence of a population at risk, Zona da Mata reported 42.3% of the municipalities in the most vulnerable group. In the joint analysis of data, the Jequitinhonha, Vale do Mucuri and Vale do Rio Doce mesoregions were the most vulnerable in the state of MG. Thus, through the outlined profile, the present study proved how socioeconomic diversity affects the vulnerability of the municipalities to face COVID-19 outbreak, highlighting the need for interventions directed to each reality.

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Faculty Opinions recommendation of The international limits and population at risk of Plasmodium vivax transmission in 2009.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.5133959.14726297 ◽

2011 ◽

Author(s):

Patrick Duffy

Keyword(s):

At Risk ◽

Plasmodium Vivax ◽

Population At Risk

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Penyelidikan KLB keracunan makanan acara ruwahan di desa Mulo, Gunung Kidul provinsi DIY

Berita Kedokteran Masyarakat ◽

10.22146/bkm.37616 ◽

2018 ◽

pp. 1

Author(s):

Mur Prasetyaningrum ◽

Z. Chomariyah ◽

Trisno Agung Wibowo

Keyword(s):

At Risk ◽

Total Population ◽

Total Coliform ◽

Case Control ◽

P Value ◽

Common Source ◽

Population At Risk ◽

E Coli

Tujuan: Studi ini untuk mengetahui gambaran KLB keracunan pangan yang terjadi di desa Mulo menurut deskripsi epidemiologi, faktor risiko dan penyebab KLB keracunan makanan. Metode: Studi ini menggunakan studi analitik case control, dimana kasus adalah orang yang mengalami sakit pada tanggal 7 - 8 Mei 2017, tinggal di desa Mulo dan mengkonsumsi makanan olahan dari bapak S dan K. Instrument menggunakan kuesioner. Hasil: KLB terjadi di Desa Mulo RT 5 dan 6 dengan jumlah kasus sebanyak 18 orang dari total population at risk 112 orang dengan gejala utama diare (100%), mual (72,2%), demam (66,6%), pusing (66,6%) dan muntah (50%). Dari diagnosa banding menurut gejala, masa inkubasi dan agent penyebab keracunan, kecurigaan kontaminasi bakteri mengarah pada E. Coli (ETEC). Masa inkubasi 1-16 jam (rata-rata 9 jam) dan common source curve. Penyaji makanan ada dua (pak K dan pak S). Dari perhitungan AR, berdasarkan sumber makanan mengarah pada makanan dari pak S (AR=42,8%). Bedasarkan menu, perhitungan OR dan CI 95 % jenis makanan yang dicurigai sebagai penyebab KLB adalah urap/gudangan (OR=4,33; p value0,0071) dan sayur lombok (OR=6,31; p value 0,0071). Sampel yang didapatkan adalah sampel air bersih, feses, dan muntahan penderita, sampel makanan tidak didapatkan karena keterlambatan informasi dari masyarakat. Hasil laboratorium, Total Coliform sampel air bersih melebihi ambang batas, sampel feses dan muntahan mengandung bakteri Klebsiella pneumonia.Simpulan: Terdapat 3 (tiga) faktor yang diduga sebagai penyebab keracunan pada warga Desa Mulo yaitu air bersih untuk mengolah makanan tercemar bakteri patogen, pengolahan makanan tidak hygienis dan penyajian makanan pada suhu ruang lebih dari 1 jam.

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Missing the Point in Point Prevalence: Harnessing EMR Data to Identify Epi-Linked Patients in an Outbreak Investigation

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.913 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s318-s318

Author(s):

Lisa Stancill ◽

Lauren DiBiase ◽

Emily Sickbert-Bennett

Keyword(s):

At Risk ◽

Disease Transmission ◽

Healthcare Setting ◽

Point Prevalence ◽

Positive Patient ◽

Outbreak Investigation ◽

Population At Risk ◽

Outbreak Investigations ◽

Overlap Method ◽

Prevalence Screen

Background: A critical step during outbreak investigations is actively screening for additional cases to assess ongoing transmission. In the healthcare setting, one widely used method is point-prevalence screening on the whole unit where a positive patient is housed. Although this point-prevalence approach captures the “place,” it can miss the “person” and “time” elements that define the population-at-risk. Methods: At University of North Carolina (UNC) Hospitals, we used business intelligence tools to build a query that harnesses the admission, discharge, and transfer (ADT) data from the electronic medical record (EMR). Using this data identifies every patient who overlapped in time and space with a positive patient. An additional query identifies currently admitted overlap patients and their current location. During an outbreak investigation, an analyst executes these queries in the mornings when surveillance screens are scheduled. The queries generate a list of patients to screen that are prioritized on the number of days they were in the same unit with the positive patient. This overlap methodology successfully captures the person, place, and time associated with possible disease transmission. We implemented the overlap method for the last 3 months following 1 year of point-prevalence approach screening during a novel disease outbreak at UNC Hospitals. Results: In total, 4,385 unique patients overlapped with previously identified infected or colonized patients, of which 781 (17.8%) from 40 departments were screened over 15 months. During a subsequent, currently ongoing, outbreak, we are utilizing the overlap method and in 6 weeks have already screened 161 of the 1,234 overlapping patients (13%). After 3 rounds of overlap screening, we have already been able to identify 1 additional positive patient. This patient was on the same unit as patient zero 4 months prior but was readmitted to a unit that would not have received a point-prevalence screen using the standard approach. Conclusions: Surveillance screening is a time-consuming, resource-intensive effort that requires collaboration between infection prevention, clinical staff, patients, and the laboratory. By harnessing EMR ADT data, we can better target the population at risk and more efficiently utilize resources during outbreak investigations. In addition, the overlap method fills a gap in the current CDC guidelines by focusing on patients who were on the same unit with any positive patient, including those who discharged and readmitted. Most importantly, we identified an additional positive patient that would not have been detected through a point-prevalence screen, helping us prevent further disease transmission.Funding: NoneDisclosures: None

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Effects of Criminal Sanctions on Drunk Drivers: Beyond Incarceration

Crime & Delinquency ◽

10.1177/0011128788034001002 ◽

1988 ◽

Vol 34 (1) ◽

pp. 29-42 ◽

Cited By ~ 18

Author(s):

Gerald R. Wheeler ◽

Rodney V. Hissong

Keyword(s):

At Risk ◽

Statistical Analysis ◽

Survival Time ◽

Drunk Driving ◽

Population At Risk ◽

Criminal Sanctions ◽

Drunk Drivers ◽

First Offenders ◽

Alternative Sanctions

Proponents of mandatory jail laws contend that alternative sanctions such as probation and fines have failed to modify behavior of those convicted of drunk driving (DWI). In order to test this proposition, we evaluated the effects of probation, fines, and jail sentences on DWI recidivism of a randomly selected DWI population at risk for 36 months. Utilizing survival time statistical analysis, the findings showed no significant differences in outcome among sanctions. As predicted, persons with a DWI history recidivated significantly sooner than first offenders. We conclude by advocating a policy of alternative sanctions to incarceration for drunk drivers.

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