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- Exploring forms of disaggregating Covid-19 data: an examplePublication . Leal, Maria da Conceição Dias; Oliveira, Teresa; Mukherjee, Amitava; Oliveira, AmilcarCOVID-19 data provided by Portuguese public health authorities lack consis tency in periodicity and metrics. To facilitate time series analysis, we transformed those data to achieve homogeneous periodicity and metrics. We present one method we used and assess the potential introduced bias and its impact on spatial distribution models of COVID-19 in Portugal, using spatial and non-spatial models. Comparing models fitted with transformed data to those with observed data for two specific days, we found no clear evidence of a worse fit for the disaggregated data.
- Stochastic response surface methodology: a study in the human health areaPublication . Oliveira, Teresa; Leal, Maria da Conceição Dias; Oliveira, AmilcarIn this paper we review Stochastic Response Surface Methodology as a tool for modeling uncertainty in the context of Risk Analysis. An application in the survival analysis in the breast cancer context is implemented with R software.
- On response surface modelsPublication . Leal, Maria da Conceição Dias; Oliveira, Teresa; Oliveira, Amilcar
- Mathematical and statistical modelling for assessing COVID-19 superspreader contagion: analysis of geographical heterogeneous impacts from public eventsPublication . Leal, Maria da Conceição Dias; Morgado, Leonel; Oliveira, Teresa A.During a pandemic, public discussion and decision-making may be required in face of limited evidence. Data-grounded analysis can support decision-makers in such contexts, contributing to inform public policies. We present an empirical analysis method based on regression modelling and hypotheses testing to assess events for the possibility of occurrence of superspreading contagion with geographically heterogeneous impacts. We demonstrate the method by evaluating the case of the May 1st, 2020 Demonstration in Lisbon, Portugal, on regional growth patterns of COVID-19 cases. The methodology enabled concluding that the counties associated with the change in the growth pattern were those where likely means of travel to the demonstration were chartered buses or private cars, rather than subway or trains. Consequently, superspreading was likely due to travelling to/from the event, not from participating in it. The method is straightforward, prescribing systematic steps. Its application to events subject to media controversy enables extracting well founded conclusions, contributing to informed public discussion and decision-making, within a short time frame of the event occurring.
- Potential impact of a demonstration on COVID-19 contagion: an application of a methodPublication . Leal, Maria da Conceição Dias; Morgado, Leonel; Oliveira, TeresaThere is evidence that some outdoor events may have contributed to the spread of COVID-19. We updated an empirical methodology based on regression modeling and hypothesis testing to analyze the potential impact of a demonstration that took place in Lisbon, within the scope of the ’Black Lives Matter’ context, on the contagion pattern in the region where this event occurred. We find that in the post-impact period there was no acceleration in the number of cases in the region, unlike in a prior event in the region. The proportion of counties where there was a potential impact of the event is not statistically significant. This result demonstrates that not all outdoor events contributed to the spread of COVID-19 and exemplifies how to apply the selected empirical methodology.
- Stochastic response surface methodology: a tool to risk assessmentPublication . Oliveira, Teresa; Leal, Maria da Conceição Dias; Oliveira, Amilcar