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Article ; Online: MEWAR

Aisha Aldosery / Anwar Musah / Georgiana Birjovanu / Giselle Moreno / Andrei Boscor / Livia Dutra / George Santos / Vania Nunes / Rossandra Oliveira / Tercio Ambrizzi / Tiago Massoni / Wellington Pinheiro dos Santos / Patty Kostkova

Frontiers in Public Health, Vol

Development of a Cross-Platform Mobile Application and Web Dashboard System for Real-Time Mosquito Surveillance in Northeast Brazil

2021 Volume 9

Abstract: Mosquito surveillance is a crucial process for understanding the population dynamics of mosquitoes, as well as implementing interventional programs for controlling and preventing the spread of mosquito-borne diseases. Environmental surveillance agents ... ...

Abstract	Mosquito surveillance is a crucial process for understanding the population dynamics of mosquitoes, as well as implementing interventional programs for controlling and preventing the spread of mosquito-borne diseases. Environmental surveillance agents who performing routine entomological surveys at properties in areas where mosquito-borne diseases are endemic play a critical role in vector surveillance by searching and destroying mosquito hotspots as well as collate information on locations with increased infestation. Currently, the process of recording information on paper-based forms is time-consuming and painstaking due to manual effort. The introduction of mobile surveillance applications will therefore improve the process of data collection, timely reporting, and field worker performance. Digital-based surveillance is critical in reporting real-time data; indeed, the real-time capture of data with phones could be used for predictive analytical models to predict mosquito population dynamics, enabling early warning detection of hotspots and thus alerting fieldworker agents into immediate action. This paper describes the development of a cross-platform digital system for improving mosquito surveillance in Brazil. It comprises of two components: a dashboard for managers and a mobile application for health agents. The former enables managers to assign properties to health workers who then survey them for mosquitoes and to monitor the progress of inspection visits in real-time. The latter, which is primarily designed as a data collection tool, enables the environmental surveillance agents to act on their assigned tasks of recording the details of the properties at inspections by filling out digital forms built into the mobile application, as well as details relating to mosquito infestation. The system presented in this paper was co-developed with significant input with environmental agents in two Brazilian cities where it is currently being piloted.
Keywords	mobile technology ; real-time ; surveillance ; mosquito ; environmental surveillance agents ; environmental health agents ; Public aspects of medicine ; RA1-1270
Subject code	333
Language	English
Publishing date	2021-10-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Linkage of national soil quality measurements to primary care medical records in England and Wales

Jack E. Gibson / E. Louise Ander / Mark Cave / Fiona Bath-Hextall / Anwar Musah / Jo Leonardi-Bee

Population Health Metrics, Vol 16, Iss 1, Pp 1-

a new resource for investigating environmental impacts on human health

2018 Volume 9

Abstract: Abstract Background Long-term, low-level exposure to toxic elements in soil may be harmful to human health but large longitudinal cohort studies with sufficient follow-up time to study these effects are cost-prohibitive and impractical. Linkage of ... ...

Abstract	Abstract Background Long-term, low-level exposure to toxic elements in soil may be harmful to human health but large longitudinal cohort studies with sufficient follow-up time to study these effects are cost-prohibitive and impractical. Linkage of routinely collected medical outcome data to systematic surveys of soil quality may offer a viable alternative. Methods We used the Geochemical Baseline Survey of the Environment (G-BASE), a systematic X-ray fluorescence survey of soil inorganic chemistry throughout England and Wales to obtain estimates of the concentrations of 15 elements in the soil contained within each English and Welsh postcode area. We linked these data to the residential postcodes of individuals enrolled in The Health Improvement Network (THIN), a large database of UK primary care medical records, to provide estimates of exposure. Observed exposure levels among the THIN population were compared with expectations based on UK population estimates to assess representativeness. Results Three hundred seventy-seven of three hundred ninety-five English and Welsh THIN practices agreed to participate in the linkage, providing complete residential soil metal estimates for 6,243,363 individuals (92% of all current and former patients) with a mean period of prospective computerised medical data collection (follow-up) of 6.75 years. Overall agreement between the THIN population and expectations was excellent; however, the number of participating practices in the Yorkshire & Humber strategic health authority was low, leading to restricted ranges of measurements for some elements relative to the known variations in geochemical concentrations in this area. Conclusions The linked database provides unprecedented population size and statistical power to study the effects of elements in soil on human health. With appropriate adjustment, results should be generalizable to and representative of the wider English and Welsh population.
Keywords	Environment and public health [N06] ; Residence characteristics [N06.850.505.400.800] ; Catchment area (health) [N06.850.505.400.800.200] ; Soil [D20.721] [G01.311.820] [N06.230.600] ; Elements [D01.268] ; Medical record linkage [E05.318.308.940.968] ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
Subject code	333
Language	English
Publishing date	2018-07-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning

Clarisse Lins de Lima / Ana Clara Gomes da Silva / Giselle Machado Magalhães Moreno / Cecilia Cordeiro da Silva / Anwar Musah / Aisha Aldosery / Livia Dutra / Tercio Ambrizzi / Iuri V. G. Borges / Merve Tunali / Selma Basibuyuk / Orhan Yenigün / Tiago Lima Massoni / Ella Browning / Kate Jones / Luiza Campos / Patty Kostkova / Abel Guilhermino da Silva Filho / Wellington Pinheiro dos Santos

Frontiers in Public Health, Vol

A Systematic Review

2022 Volume 10

Abstract: Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed by a ...

Abstract	Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed by a combination of climatic, environmental, and human mobility factors. Arboviruses prediction models can be a support tool for decision-making by public health agents. In this study, we propose a systematic literature review to identify arboviruses prediction models, as well as models for their transmitter vector dynamics. To carry out this review, we searched reputable scientific bases such as IEE Xplore, PubMed, Science Direct, Springer Link, and Scopus. We search for studies published between the years 2015 and 2020, using a search string. A total of 429 articles were returned, however, after filtering by exclusion and inclusion criteria, 139 were included. Through this systematic review, it was possible to identify the challenges present in the construction of arboviruses prediction models, as well as the existing gap in the construction of spatiotemporal models.
Keywords	digital epidemiology ; computational intelligence ; arboviruses forecast ; machine learning ; systematic review ; dengue ; Public aspects of medicine ; RA1-1270
Subject code	306
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An Evaluation of the OpenWeatherMap API versus INMET Using Weather Data from Two Brazilian Cities

Anwar Musah / Livia Màrcia Mosso Dutra / Aisha Aldosery / Ella Browning / Tercio Ambrizzi / Iuri Valerio Graciano Borges / Merve Tunali / Selma Başibüyük / Orhan Yenigün / Giselle Machado Magalhaes Moreno / Ana Clara Gomes da Silva / Wellington Pinheiro dos Santos / Clarisse Lins de Lima / Tiago Massoni / Kate Elizabeth Jones / Luiza Cintra Campos / Patty Kostkova

Data, Vol 7, Iss 8, p

Recife and Campina Grande

2022 Volume 106

Abstract: Certain weather conditions are inadvertently related to increased population of various mosquitoes. In order to predict the burden of mosquito populations in the Global South, it is imperative to integrate weather-related risk factors into such ... ...

Abstract	Certain weather conditions are inadvertently related to increased population of various mosquitoes. In order to predict the burden of mosquito populations in the Global South, it is imperative to integrate weather-related risk factors into such predictive models. There are a lot of online open-source weather platforms that provide historical, current and future weather forecasts which can be utilised for general predictions, and these electronic sources serve as an alternate option for weather data when physical weather stations are inaccessible (or inactive). Before using data from such online source, it is important to assess the accuracy against some baseline measure. In this paper, we therefore evaluated the accuracy and suitability of weather forecasts of two parameters namely temperature and humidity from the OpenWeatherMap API (an online weather platform) and compared them with actual measurements collected from the Brazilian weather stations (INMET). The evaluation was focused on two Brazilian cites, namely, Recife and Campina Grande. The intention is to prepare an early warning model which will harness data from OpenWeatherMap API for mosquito prediction.
Keywords	weather ; meteorological parameters ; data sources ; OpenWeatherMap ; application programming interfaces ; Bibliography. Library science. Information resources ; Z
Subject code	333
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: What are the drivers of recurrent cholera transmission in Nigeria? Evidence from a scoping review

Kelly Osezele Elimian / Somto Mezue / Anwar Musah / Oyeronke Oyebanji / Ibrahima Soce Fall / Sebastian Yennan / Michel Yao / Patrick Okumu Abok / Nanpring Williams / Lynda Haj Omar / Thieno Balde / Kobina Ampah / Ifeanyi Okudo / Luka Ibrahim / Arisekola Jinadu / Wondimagegnehu Alemu / Clement Peter / Chikwe Ihekweazu

BMC Public Health, Vol 20, Iss 1, Pp 1-

2020 Volume 13

Abstract: Abstract Background The 2018 cholera outbreak in Nigeria affected over half of the states in the country, and was characterised by high attack and case fatality rates. The country continues to record cholera cases and related deaths to date. However, ... ...

Abstract	Abstract Background The 2018 cholera outbreak in Nigeria affected over half of the states in the country, and was characterised by high attack and case fatality rates. The country continues to record cholera cases and related deaths to date. However, there is a dearth of evidence on context-specific drivers and their operational mechanisms in mediating recurrent cholera transmission in Nigeria. This study therefore aimed to fill this important research gap, with a view to informing the design and implementation of appropriate preventive and control measures. Methods Four bibliographic literature sources (CINAHL (Plus with full text), Web of Science, Google Scholar and PubMed), and one journal (African Journals Online) were searched to retrieve documents relating to cholera transmission in Nigeria. Titles and abstracts of the identified documents were screened according to a predefined study protocol. Data extraction and bibliometric analysis of all eligible documents were conducted, which was followed by thematic and systematic analyses. Results Forty-five documents met the inclusion criteria and were included in the final analysis. The majority of the documents were peer-reviewed journal articles (89%) and conducted predominantly in the context of cholera epidemics (64%). The narrative analysis indicates that social, biological, environmental and climatic, health systems, and a combination of two or more factors appear to drive cholera transmission in Nigeria. Regarding operational dynamics, a substantial number of the identified drivers appear to be functionally interdependent of each other. Conclusion The drivers of recurring cholera transmission in Nigeria are diverse but functionally interdependent; thus, underlining the importance of adopting a multi-sectoral approach for cholera prevention and control.
Keywords	Cholera ; Scoping review ; Drivers ; Transmission ; Multi-sectoral ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2020-04-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Identifying and quantifying the factors associated with cholera-related death during the 2018 outbreak in Nigeria

The Pan African Medical Journal, Vol 37, Iss

2020 Volume 368

Abstract: INTRODUCTION: Cholera outbreaks in Nigeria are often associated with high case fatality rates; however, there is a dearth of evidence on context-specific factors associated with the trend. This study therefore aimed to identify and quantify the factors ... ...

Abstract	INTRODUCTION: Cholera outbreaks in Nigeria are often associated with high case fatality rates; however, there is a dearth of evidence on context-specific factors associated with the trend. This study therefore aimed to identify and quantify the factors associated with cholera-related deaths in Nigeria. METHODS: Using a cross-sectional design, we analysed surveillance data from all the States that reported cholera cases during the 2018 outbreak, and defined cholera-related death as death of an individual classified as having cholera according to the Nigeria Centre for Disease Control case definition. Factors associated with cholera-related death were assessed using multivariable logistic regression and findings presented as adjusted odds ratios (ORs) with 95% Confidence Intervals (95% CIs). RESULTS: Between January 1 and November 19, 2018, 41,394 cholera cases were reported across 20 States, including 815 cholera-related deaths. In the adjusted multivariable model, older age, male gender, living in peri-urban areas or in flooded states, infection during the rainy season, and delay in seeking health care by >2 days were positively associated with cholera-related death; whereas living in urban areas, hospitalisation in the course of illness, and presentation to a secondary hospital were negatively associated with cholera-related death. CONCLUSION: Cholera-related deaths during the 2018 outbreak in Nigeria appeared to be driven by multiple factors, which further reemphasises the importance of adopting a multisectoral approach to the design and implementation of context-specific interventions in Nigeria.
Keywords	factors ; cholera ; case fatality rate ; death ; outbreak ; multi-sectoral ; nigeria ; Medicine ; R
Subject code	610
Language	English
Publishing date	2020-12-01T00:00:00Z
Publisher	The Pan African Medical Journal
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Cecilia Cordeiro da Silva / Clarisse Lins de Lima / Ana Clara Gomes da Silva / Eduardo Luiz Silva / Gabriel Souza Marques / Lucas Job Brito de Araújo / Luiz Antônio Albuquerque Júnior / Samuel Barbosa Jatobá de Souza / Maíra Araújo de Santana / Juliana Carneiro Gomes / Valter Augusto de Freitas Barbosa / Anwar Musah / Patty Kostkova / Wellington Pinheiro dos Santos / Abel Guilhermino da Silva Filho

Frontiers in Public Health, Vol

2021 Volume 9

Abstract: Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, ... ...

Abstract	Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus.Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics.Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%.Conclusion: Spatio-temporal analysis provided a broader assessment ...
Keywords	COVID-19 ; SARS-CoV-2 ; Covid-19 pandemics forecasting ; spatio-temporal analysis ; spatio-temporal forecasting ; digital epidemiology ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2021-04-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Descriptive epidemiology of cholera outbreak in Nigeria, January–November, 2018

BMC Public Health, Vol 19, Iss 1, Pp 1-

implications for the global roadmap strategy

2019 Volume 11

Abstract: Abstract Background The cholera outbreak in 2018 in Nigeria reaffirms its public health threat to the country. Evidence on the current epidemiology of cholera required for the design and implementation of appropriate interventions towards attaining the ... ...

Abstract	Abstract Background The cholera outbreak in 2018 in Nigeria reaffirms its public health threat to the country. Evidence on the current epidemiology of cholera required for the design and implementation of appropriate interventions towards attaining the global roadmap strategic goals for cholera elimination however seems lacking. Thus, this study aimed at addressing this gap by describing the epidemiology of the 2018 cholera outbreak in Nigeria. Methods This was a retrospective analysis of surveillance data collected between January 1st and November 19th, 2018. A cholera case was defined as an individual aged 2 years or older presenting with acute watery diarrhoea and severe dehydration or dying from acute watery diarrhoea. Descriptive analyses were performed and presented with respect to person, time and place using appropriate statistics. Results There were 43,996 cholera cases and 836 cholera deaths across 20 states in Nigeria during the outbreak period, with an attack rate (AR) of 127.43/100,000 population and a case fatality rate (CFR) of 1.90%. Individuals aged 15 years or older (47.76%) were the most affected age group, but the proportion of affected males and females was about the same (49.00 and 51.00% respectively). The outbreak was characterised by four distinct epidemic waves, with higher number of deaths recorded in the third and fourth waves. States from the north-west and north-east regions of the country recorded the highest ARs while those from the north-central recorded the highest CFRs. Conclusion The severity and wide-geographical distribution of cholera cases and deaths during the 2018 outbreak are indicative of an elevated burden, which was more notable in the northern region of the country. Overall, the findings reaffirm the strategic role of a multi-sectoral approach in the design and implementation of public health interventions aimed at preventing and controlling cholera in Nigeria.
Keywords	Cholera ; Outbreak ; Attack rate ; Case fatality rate ; Global roadmap ; Nigeria ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2019-09-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: COVID-19 mortality rate and its associated factors during the first and second waves in Nigeria.

Kelly Elimian / Anwar Musah / Carina King / Ehimario Igumbor / Puja Myles / Olaolu Aderinola / Cyril Erameh / William Nwanchukwu / Oluwatosin Akande / Ndembi Nicaise / Oladipo Ogunbode / Abiodun Egwuenu / Emily Crawford / Giulia Gaudenzi / Ismail Abdus-Salam / Olubunmi Olopha / Yahya Disu / Abimbola Bowale / Cyprian Oshoma /

Cornelius Ohonsi / Chinedu Arinze / Sikiru Badaru / Blessing Ebhodaghe / Zaiyad Habib / Michael Olugbile / Chioma Dan-Nwafor / Jafiya Abubakar / Emmanuel Pembi / Lauryn Dunkwu / Ifeanyi Ike / Ekaete Tobin / Bamidele Mutiu / Rejoice Luka-Lawal / Obinna Nwafor / Mildred Okowa / Chidiebere Ezeokafor / Emem Iwara / Sebastian Yennan / Sunday Eziechina / David Olatunji / Lanre Falodun / Emmanuel Joseph / Ifeanyi Abali / Tarik Mohammed / Benjamin Yiga / Khadeejah Kamaldeen / Emmanuel Agogo / Nwando Mba / John Oladejo / Elsie Ilori / Olusola Aruna / Geoffrey Namara / Stephen Obaro / Khadeejah Hamza / Michael Asuzu / Shaibu Bello / Friday Okonofua / Yusuf Deeni / Ibrahim Abubakar / Tobias Alfven / Chinwe Ochu / Chikwe Ihekweazu

PLOS Global Public Health, Vol 2, Iss 6, p e

2022 Volume 0000169

Abstract: COVID-19 mortality rate has not been formally assessed in Nigeria. Thus, we aimed to address this gap and identify associated mortality risk factors during the first and second waves in Nigeria. This was a retrospective analysis of national surveillance ... ...

Abstract	COVID-19 mortality rate has not been formally assessed in Nigeria. Thus, we aimed to address this gap and identify associated mortality risk factors during the first and second waves in Nigeria. This was a retrospective analysis of national surveillance data from all 37 States in Nigeria between February 27, 2020, and April 3, 2021. The outcome variable was mortality amongst persons who tested positive for SARS-CoV-2 by Reverse-Transcriptase Polymerase Chain Reaction. Incidence rates of COVID-19 mortality was calculated by dividing the number of deaths by total person-time (in days) contributed by the entire study population and presented per 100,000 person-days with 95% Confidence Intervals (95% CI). Adjusted negative binomial regression was used to identify factors associated with COVID-19 mortality. Findings are presented as adjusted Incidence Rate Ratios (aIRR) with 95% CI. The first wave included 65,790 COVID-19 patients, of whom 994 (1∙51%) died; the second wave included 91,089 patients, of whom 513 (0∙56%) died. The incidence rate of COVID-19 mortality was higher in the first wave [54∙25 (95% CI: 50∙98-57∙73)] than in the second wave [19∙19 (17∙60-20∙93)]. Factors independently associated with increased risk of COVID-19 mortality in both waves were: age ≥45 years, male gender [first wave aIRR 1∙65 (1∙35-2∙02) and second wave 1∙52 (1∙11-2∙06)], being symptomatic [aIRR 3∙17 (2∙59-3∙89) and 3∙04 (2∙20-4∙21)], and being hospitalised [aIRR 4∙19 (3∙26-5∙39) and 7∙84 (4∙90-12∙54)]. Relative to South-West, residency in the South-South and North-West was associated with an increased risk of COVID-19 mortality in both waves. In conclusion, the rate of COVID-19 mortality in Nigeria was higher in the first wave than in the second wave, suggesting an improvement in public health response and clinical care in the second wave. However, this needs to be interpreted with caution given the inherent limitations of the country's surveillance system during the study.
Keywords	Public aspects of medicine ; RA1-1270
Subject code	310
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: COVID-SGIS

Clarisse Lins de Lima / Cecilia Cordeiro da Silva / Ana Clara Gomes da Silva / Eduardo Luiz Silva / Gabriel Souza Marques / Lucas Job Brito de Araújo / Luiz Antônio Albuquerque Júnior / Samuel Barbosa Jatobá de Souza / Maíra Araújo de Santana / Juliana Carneiro Gomes / Valter Augusto de Freitas Barbosa / Anwar Musah / Patty Kostkova / Wellington Pinheiro dos Santos / Abel Guilhermino da Silva Filho

Frontiers in Public Health, Vol

A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19

2020 Volume 8

Abstract: Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To ... ...

Abstract	Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil.Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented.Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, Maranhão, Piauí, Rio Grande do Norte, Amapá, Rondônia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for Espírito Santo, Minas Gerais, Paraná, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%.Conclusion: The proposed method for dynamic forecasting may be used to guide social policies ...
Keywords	SARS-CoV-2 spread forecast ; intelligent forecasting systems ; infectious diseases ; dynamic forecasting systems ; Covid-19 forecasting ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2020-11-01T00:00:00Z
Publisher	Frontiers Media S.A.
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Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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