COVID-19 : nothing is normal in this pandemic

Funding: This work was partially support by CEAUL (funded by FCT – Fundação para a Ciência e a Tecnologia, Portugal, through the project UIDB/00006/2020).This manuscript brings attention to inaccurate epidemiological concepts that emerged during the COVID-19 pandemic. In social media and scientific journals, some wrong references were given to a "normal epidemic curve" and also to a "log-normal curve/distribution". For many years, textbooks and courses of reputable institutions and scientific journals have disseminated misleading concepts. For example, calling histogram to plots of epidemic curves or using epidemic data to introduce the concept of a Gaussian distribution, ignoring its temporal indexing. Although an epidemic curve may look like a Gaussian curve and be eventually modelled by a Gauss function, it is not a normal distribution or a log-normal, as some authors claim. A pandemic produces highly-complex data and to tackle it effectively statistical and mathematical modelling need to go beyond the "one-size-fits-all solution". Classical textbooks need to be updated since pandemics happen and epidemiology needs to provide reliable information to policy recommendations and actions.Publisher PDFPeer reviewe

Religious affiliation modulates weekly cycles of cropland burning in Sub-Saharan Africa

Research ArticleVegetation burning is a common land management practice in Africa, where fire is used for hunting, livestock husbandry, pest control, food gathering, cropland fertilization, and wildfire prevention. Given such strong anthropogenic control of fire, we tested the hypotheses that fire activity displays weekly cycles, and that the week day with the fewest fires depends on regionally predominant religious affiliation.We also analyzed the effect of land use (anthrome) on weekly fire cycle significance. Fire density (fire counts.km-2) observed per week day in each region was modeled using a negative binomial regression model, with fire counts as response variable, region area as offset and a structured random effect to account for spatial dependence. Anthrome (settled, cropland, natural, rangeland), religion (Christian, Muslim, mixed) week day, and their 2-way and 3-way interactions were used as independent variables. Models were also built separately for each anthrome, relating regional fire density with week day and religious affiliation. Analysis revealed a significant interaction between religion and week day, i.e. regions with different religious affiliation (Christian, Muslim) display distinct weekly cycles of burning. However, the religion vs. week day interaction only is significant for croplands, i.e. fire activity in African croplands is significantly lower on Sunday in Christian regions and on Friday in Muslim regions. Magnitude of fire activity does not differ significantly among week days in rangelands and in natural areas, where fire use is under less strict control than in croplands. These findings can contribute towards improved specification of ignition patterns in regional/global vegetation fire models, and may lead to more accurate meteorological and chemical weather forecastinginfo:eu-repo/semantics/publishedVersio

Mean MODIS active fire regional density (fires.km^-2), 2003–2011.

<p>a) Monday; b) Tuesday; c) Wednesday; d) Thursday; e) Friday; f) Saturday; g) Sunday.</p

Deviance Information Criterion (DIC) scores for all negative binomial models fitted.

<p>R–Religion; W–Week day; A–Anthrome; ICAR–Intrinsic conditional autoregressive term.</p><p>The best model (lowest DIC, bold) includes all single variables, the two-way interactions between religion and week day, between religion and anthrome, and the spatial term.</p

Number of regions by dominant religion and dominant anthrome.

<p>Number of regions by dominant religion and dominant anthrome.</p

Mean MODIS active fire density (fires.km^-2) per week day.

<p>a) All anthromes; b) Croplands. Solid line: Christian regions; Large dashed line: Muslim regions; Fine dashed line: mixed Christian-Muslim regions.</p