Climate and Covid-19-Upgrade and solar radiation in uences based on Brazil cases

Francisco Mendonça (  chico@ufpr.br ) Universidade Federal do Parana Setor de Ciencias da Terra https://orcid.org/0000-0002-3107-8519 Max Anjos Universidade Federal do Parana Setor de Ciencias da Terra Erika Collischonn Universidade Federal de Pelotas Pedro Murara Universidade Federal da Fronteira do Sul Deise Ely F. Universidade Estadual de Londrina Leila Limberger Universidade Estadual do Oeste do Paraná Lindberg Nascimento Universidade Federal de Santa Catarina Centro de Filoso a e Ciencias Humanas Gilson C. F. da Cruz Universidade Estadual de Ponta Grossa Wilson Roseghini Universidade Federal do Parana Aparecido R. Andrade Universidade Estadual do Centro do Paraná


Introduction
The novel Coronavirus (SARS-CoV-2) causes the historic pandemic of COVID-19. More than 4,8 million con rmed cases and over 323 thousand deaths worldwide, as May 20, 2020 (WHO, 2020). COVID-19 has spread rapidly across nearly all regions of the world, mainly due to its highly communicable nature and intense human mobility on a global scale. Many uncertainties and considerable ignorance remain regarding both the viral dynamics, control of transmission and treatment of the COVID-19.
The currently challenge puts in motion the multicausality as framework for analysis of the COVID -19 pandemic. The interaction between the physical-natural environment, social environment (way of life, mobility, urbanization, public policies, occupation density) and living environment (virus) has been bestdocumented (Besancenot, 2001;Sorre, 1951). Epidemiology suggests the climate and meteorological as environmental factors that have seasonal in uence on viral diseases (National Academies of Sciences, 2020), either indirectly on individuals and human populations or directly on vectors and/or pathogens.
SARS-CoV-2 is part of a large viral family, of which four species are best known for the occurrence of common colds: i) Alpha coronavirus HCoV-229E (infecting humans and bats), ii) Alpha coronavirus HCoV-NL63, iii) Beta coronavirus HCoV-OC43 and, iv) Beta coronavirus HCoV-HKU1 (originating from infected rats) that are highly associated with climatic conditions and meteorological factors (Matoba et al., 2018).
Recent study showed that SARS-CoV-2 is highly stable at 4.0 °C, but sensitive to heat, so that with the incubation temperature increased to 70 °C, the time for virus inactivation was reduced to 5 min (Chin et al., 2020). Although recent researches have provided pioneering insights into the transmission of COVID- In this study, (i) we upgraded the available literature surround climate and COVID-19, highlighting the main climatological variables that may affect this disease, and (ii) we emphasized the relationship between the COVID-19 outbreak and climato-meteorological parameters in six capital Brazilian cities.

Methodology
Literature review procedure It was updated the publications available on the climate and COVID-19 using Scopus, Web of Science, and PubMed database from January 1 to May 20, 2020. The search terms used into the database were "COVID-19" OR "Coronavirus" OR "Corona virus" OR "2019-nCoV" OR "SARS-CoV" OR "MERS-CoV" OR "Severe Acute Respiratory Syndrome" OR "Middle East Respiratory Syndrome", in combination with AND "Climate" AND "meteorological". English review articles and research articles were considered as search lters. In this review, the preprint (no peer-review) papers were considered because an initial assessing of the dataset, methods and potential scienti c contribution showed that their outcomes are similar to selected peer-reviewed articles. where n is the hours of bright sunshine, N is the bright sunshine to potential bright sunshine, and Rs/Ra is the estimated ratio of surface to extraterrestrial solar radiation (MJ m 2 day − 1 ). The daily values of solar brightness are related to the radiation and potential hours of sunshine relative to latitude and season (Snyder, 2001). Geospatially daily average amount of the total solar radiation at each city were extracted from the POWER Data Access Viewer (DAV) Web Mapping Application managed by the NASA Langley

Dataset and statistical analysis
Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program.
Regarding the COVID-19 data, it was used the number daily of con rmed cases from Brazil-IO web platform (https://brasil.io/dataset/covid19/caso/), a collaborative project that manages bulletin and reporting of the coronavirus cases noticed by the municipal governments and Brazilian Health Ministry.
As we recognized that there is a signi cant inaccuracy between the number of real COVID-19 cases and noti ed ones (underreporting) in Brazilian context, we used three sampled periods to the climatic parameters data, as follows: i) without time lag (CC1), (ii) a week of time lag (CC7), and (iii) two weeks of time lag (CC14). CC1 refers to daily values of COVID-19 cases as published o cially, CC7 meets the epidemiological week, and CC14 is related with initial infection SAR-COV-2 period.
The Shapiro-Wilk and Anderson-Darling tests were applied to evaluate whether the sampled of data follows a normality distribution. Table 1 shows most cites had not a normal distribution (p-value < 0,005), suggesting the application of multicollinearity. This test evaluates when relative signi cant correlation coe cients can not represent the intensity, in which an independent variable is to able to explain the dependent variables.  Xie and Zhu, 2020). The emphasis of these studies has been placed on the establishment of thresholds, or climatic optimum, extracted from statistical associations between meteorological parameters measured in meteorological stations (outdoor environment) or controlled in laboratories (indoor environment) and con rmed cases of COVID-19 (and other types of Coronavirus) ( Table 2). Even though, 90% of COVID-19 cases from countries located at latitudes above 30ºN had been reported in places with AH below 9 g/m 3 (Bukhari and Jameel, 2020), the daily reduction in COVID-19 mortality cases was associated with high levels of AH (

Descriptive analysis
The correlation coe cient values from multicollinearity test showed most cities have a strong correlation between climatic and number of COVID-19 cases for CC2 and CC14 periods, as illustrated in Table 2 Overall, these results suggest that the climatic parameters had greater association with variation of exponential curve of COVID-19 cases were Tmax, Tmin, DPmax followed by SR and WS. Further studies are needed to address the integrated climatic variable analysis, e.g., the types of weather and COVID-19 cases. It was highlighted the time lag of CC14 revealed a suitable way to evaluate the correlation between number of COVID-19 cases and climatic parameters, as shown in Table 3.  Since mid-March this year, new cases of COVID-19 from community spread have been con rmed in Brazilian cities in almost all regions of the country all in hot and humid regions ( Table 4). The rst records of autochthonous transmission of COVID-19 in these cities occurred during the summer and beginning of the southern autumn. The maximum monthly average Ta (above 30.0ºC) in the period between January and April 2020 in these cities suggests that high Ta, even in this seasonality, may not limit the survival and transmission of SARS-CoV-2 in tropical environments. The fact that these cities reported the initial phase of pandemic in the middle of summer and in the early autumn encourages the development of new studies in the coming weeks and months, since Ta has not yet proved to be limiting to the spread of the SARS-CoV-2. Note: *Climatic groups according to Köppen-Geiger climate classi cation. ** Data refer to the states, whereas most cases were registered in the capital cities. ***Lethality rate obtained by the ratio between 1000 con rmed cases and the number of deaths.
These results suggest the transmission and contagion by SARS-CoV-2 seem to have been enhanced under from medium to low DSR. Ahmadi et al., (2020) also found high rate of infection of COVID-19 associated with low SR in ve Iranian providences. Sagripanti (2007) reported that the inactivation of viruses in the environment by high solar ultraviolet radiation (UV-C) plays a role in the seasonal occurrence of in uenza pandemics. We suggest the need for studies and immediate advances regarding the in uence of insolation on the ecology of the vector related to SARS-CoV-2, a fact that may affect public policies and coordinated actions to reduce and control of COVID-19.

Conclusion
Climate conditions are one of the environmental factors that in uence the ecology and pathogens of living beings, such as the Coronavirus (SARS-CoV-2). The literature review related to climate and COVID-19 was upgraded and revealed that air temperature (Ta), relative humidity (RH) and absolute humidity (AH) to be three main climatic and meteorological variables that have been most used to study the in uence of climate on the SARS-CoV-2 (and other in uenza-like viruses), since the beginning of the COVID-19 pandemic. However, Ta, RH and AH alone do not able to explain the variation of number of COVID-19 cases and predict its behavior to different climatic zones because the thresholds of these parameters, that could result in the establishment of an optimal climate for transmission and contagion of SARS-CoV-2, are still unde ned.
In accordance with previous studies, we observed the initial and increasing of number COVID-19 cases was associated with Low L ratio in six capital Brazilian cities, suggesting a possible effect of L on the transmission of SARS-CoV-2 by outdoor environment.
With a basis in multicausality, this paper contributes to a better understanding of COVID-19, which, in the absence of studies and measures to contain this serious pandemic, can act towards the control of viral transmission. Given its urgency, it behooves us to expand our knowledge concerning the virus. It is hoped that the information we have presented can contribute to this expansion.

Competing interests
The authors declare that they have no competing interests.
Author's contributions A analyzed data re-review the manuscript. All authors read and approved the nal manuscript.