COVID-19 in Piauí: initial scenario and perspectives for coping

Batista, Francisca Miriane de Araújo; Mascarenhas, Márcio Dênis Medeiros; Marinelli, Natália Pereira; Albuquerque, Layana Pachêco de Araújo; Mascarenhas, Márcio Dênis Medeiros; Vieira, Marcelo Adriano da Cunha e Silva; Sousa, Isaura Danielli Borges de

doi:10.1590/0037-8682-0175-2020

Cited by 8 publications

(10 citation statements)

References 6 publications

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“…However, this study did not consider the other factors that are reported to influence the spread of virus related to other weather parameters, epidemiology and demography (Tian et al 2020;Borjas 2020;Zhong et al 2020). There can be scores of unknown factors and processes that govern the pandemic's spread but are yet to be researched out due to the lack of credible data (Batista et al 2020;Peng et al 2020;Tang et al 2020). Hence, any assumption about the factors that determine the spread of COVID-19 would lack any prudency.…”

Section: Introductionmentioning

confidence: 97%

Coronavirus pandemic versus temperature in the context of Indian subcontinent: a preliminary statistical analysis

Meraj

Farooq

Singh

et al. 2020

Environ Dev Sustain

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The novel coronavirus (COVID-19) has unleashed havoc across different countries and was declared a pandemic by the World Health Organization. Since certain evidences indicate a direct relationship of various viruses with the weather (temperature in particular), the same is being speculated about COVID-19; however, it is still under investigation as the pandemic is advancing the world over. In this study, we tried to analyze the spread of COVID-19 in the Indian subcontinent with respect to the local temperature regimes from March 9, 2020, to May 27, 2020. To establish the relation between COVID-19 and temperature in India, three different ecogeographical regions having significant temperature differences were taken into consideration for the analysis. We observed that except Maharashtra, Rajasthan and Kashmir showed a significantly positive correlation between the number of COVID-19 cases and the temperature during the period of study. The evidences based on the results presented in this research lead us to believe that the increasing temperature is beneficial to the COVID-19 spread, and the cases are going to rise further with the increasing temperature over India. We, therefore, conclude that the existing data, though limited, suggest that the spread of COVID-19 in India is not explained by the variation of temperature alone and is most likely driven by a host of other factors related to epidemiology, socioeconomics and other climatic factors. Based on the results, it is suggested that temperature should not be considered as a yardstick for planning intervention strategies for controlling the COVID-19 pandemic.

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Section: Introductionmentioning

confidence: 97%

Coronavirus pandemic versus temperature in the context of Indian subcontinent: a preliminary statistical analysis

Meraj

Farooq

Singh

et al. 2020

Environ Dev Sustain

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“…As cidades de Piripiri e Altos apresentam alta letalidade, levando em conta o número de casos confirmados na cidade, tendo como base o número observado em Teresina, uma vez que apresentam letalidade próximas, mas com a diferença de casos confirmados muito discrepantes, isso pode ser explicado pelo motivo de ser uma cidade com menos aporte financeiro que Teresina (Marinelli et al, 2020) e, por este fato, pode apresentar maiores dificuldades estruturais de tratamento do vírus. Também pode ser justificado por ter pessoas com número maiores de comorbidades por motivos sociodemográficos presentes nessa região adjacente ("Painel Covid-19 • Piauí › Página 1," n.d.).…”

Section: Metodologiaunclassified

Perfil epidemiológico da morbimortalidade da Covid-19 no Estado do Piauí: uma atualização do cenário atual

Silva

et al. 2020

RSD

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O novo Coronavírus foi definido como SARS-CoV-2 no fim de 2019. Ele é responsável pela a doença classificada como COVID-19. O presente estudo teve como objetivo discutir os óbitos provocados pela covid-19 no estado do Piauí durante a pandemia, e sua correlação com as comorbidades associadas aos pacientes e sua faixa etária. Trata-se de uma pesquisa descritiva, executada a partir do levantamento epidemiológico dos casos e óbitos da Covid-19 no Estado do Piauí. Foi analisada a faixa etária, comorbidades e fatores de risco identificados entre os óbitos, onde a partir desses dados, foi calculado a letalidade e plotados em tabelas. O estado do Piauí apresenta 10.153 mil casos confirmados, tendo a capital Teresina, com o maior número, com 43% dos casos seguido da cidade litorânea de Parnaíba com 13%, Barras 4%, Campo maior 3% e Picos 3%. Teresina ainda apresentou o maior número de óbitos com 196 mortes, seguido de Parnaíba (n=31), Barras (n=8), Campo maior (n=7), Picos, Esperantina e Piripiri (n=6). As cardiopatias tiveram a maior frequência nos casos de óbitos por Covid-19, com 48,61% dos casos, seguido da diabetes com 23,61%, DNC ou DNM 4,63%, Obesidade 3,7%. A faixa etária de 70 a 79 anos a mais acometida com 30%, seguido de 80 anos ou mais com 26,67%. Assim, pode-se inferir o quão é imprescindível o desenvolvimento estrutural da saúde pública no Piauí, sobretudo, nos centros emergentes, bem como a preservação prioritária das pessoas que possuem comorbidades e com faixa etária alta.

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“…In this difficult epidemiological scenario, there is a clear expectation of witnessing a measles, dengue and COVID‐19 syndemic, among other conditions that afflict the Brazilian people. In this context, the healthcare system, especially in the northeast and northern Brazil, is not prepared to face this pandemic that is growing at alarming rates across the world 3 . As an example, when the pandemic hit Maranhão, a northern very low‐income state located in Amazonia, with 6.8 million population, it had only 232 intensive care beds, concentrated in just three cities.…”

Section: Cases Deaths Incidence Mortalitymentioning

confidence: 99%

“…In this context, the healthcare system, especially in the northeast and northern Brazil, is not prepared to face this pandemic that is growing at alarming rates across the world. 3 As an example, when the pandemic hit Maranhão, a northern very low-income state located in Amazonia, with 6.8 million population, it had only 232 intensive care beds, concentrated in just three cities. After hustling to build out capacity, it has 761 ICU beds and offers some level of intensive care in 11 cities, according to state authorities.…”

mentioning

confidence: 99%