Prioritizing the first doses of SARS-CoV-2 vaccine to save the elderly: the case study of Italy

Many countries are currently facing high mortality caused by the circulation of SARS-CoV-2 among the elderly not yet vaccinated. Vaccine shortage poses relevant challenges to health authorities, called to act in a timely manner, and with scarcity of vaccine, and data. We have developed a model for estimating of the impact of vaccination on the mortality of the elderly following a schedule of mRNA SARS-CoV-2 vaccine that prioritize first dose administration, as alternative to the standard schedule of two doses administered 3 to 4 weeks apart. We studied the Italian scenario, considering it representative of other Countries facing similar conditions in terms of virus circulation, mortality, and vaccine shortage, in the period from February 10 to April 14 2021. Under different conditions of quantity of vaccine administration, the schedule prioritizing first doses showed always significant increase of protected individuals, and a decrease of deaths, up to 19.8% less than the standard schedule. These findings support the vaccination option of prioritizing first dose in the elderly until vaccine supplies are adequate.

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Prioritizing the First Doses of SARS-CoV-2 Vaccine to Save the Elderly: The Case Study of Italy

Frontiers in Public Health ◽

10.3389/fpubh.2021.684760 ◽

2021 ◽

Vol 9 ◽

Author(s):

Giuseppe Pontrelli ◽

Giulio Cimini ◽

Marco Roversi ◽

Andrea Gabrielli ◽

Gaetano Salina ◽

...

Keyword(s):

The Elderly ◽

European Countries ◽

Mortality Reduction ◽

Dose Administration ◽

Health Authorities ◽

Vaccination Campaigns ◽

Vaccine Shortage

SARS-CoV-2 is currently causing hundreds of deaths every day in European countries, mostly in not yet vaccinated elderly. Vaccine shortage poses relevant challenges to health authorities, called to act promptly with a scarcity of data. We modeled the mortality reduction of the elderly according to a schedule of mRNA SARS-CoV-2 vaccine that prioritized first dose administration. For the case study of Italy, we show an increase in protected individuals up to 53.4% and a decrease in deaths up to 19.8% in the cohort of over 80's compared with the standard vaccine recalls after 3 or 4 weeks. This model supports the adoption of vaccination campaigns that prioritize the administration of the first doses in the elderly.

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The Effects of Gentrification on the Elderly: A Case Study in the City of Cáceres

Social Sciences ◽

10.3390/socsci9090154 ◽

2020 ◽

Vol 9 (9) ◽

pp. 154

Author(s):

Lidia Domínguez-Parraga

Keyword(s):

Social Space ◽

Methodological Approach ◽

Well Being ◽

The Elderly ◽

Large Cities ◽

Social And Emotional ◽

The Impact ◽

The City

This study aims to analyze the consequences of the gentrification process as a result of tourism on the elderly inhabitants. Firstly, the concept of gentrification is reviewed, a process that is no longer exclusive to large cities but has spread to smaller and lesser-known municipalities. A clear example of this type of new tourist destination is the city of Cáceres, a World Heritage medium-sized city where tourism is the basis of its economy. The research considers gentrification in medium-sized cities and its effect on active aging. Based on a qualitative methodological approach, a total of 32 in-depth interviews were conducted and analyzed to compare two neighborhoods—one gentrified and one not. The results show a remarkable disparity in the residents’ perceptions of their environment and their city. The findings suggest adverse effects on the quality of aging due to the gentrification process, such as family dependency, social-space disconnection, and a generally pessimistic image of the neighborhood. Consequently, the impact of tourism negatively affects the gentrified neighborhood inhabitants’ psychological, social, and emotional well-being.

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Measurement of spatial equity : a case study of nursing institution

10.47472/bgdi1793 ◽

2019 ◽

Author(s):

Xin Sui ◽

◽

Yifan Yu ◽

Liu Huhui ◽

◽

...

Keyword(s):

Spatial Distribution ◽

Spatial Autocorrelation ◽

Supply And Demand ◽

The Elderly ◽

Spatial Dimension ◽

Spatial Equity ◽

Public Resources ◽

Local Moran ◽

The Impact

Equity and justice have always been important norms in the field of urban planning. With the gradual deepening of understanding of residential environment, the research context of equity and justice related to location is becoming more and more sophisticated. Recently, varieties of subjects Including Public Health and Geography focus on the inequity of public resources in spatial distribution and how to measure the degree of this gap. In general, the mainstream measurement methods can be summarized into two categories: (1) The description of phenomenon caused by the spatial inequities, and accessibility is a typical method of this type. (2) the direct quantification of inequity, such as Gink Coefficient which is originated from the economics field and introduced into the measurement of health equity, and Getis-Ord General G, together with Moran’ index is the most commonly method used into the general spatial autocorrelation. In this paper, based on the overall literature review of the concept of equity in the study using these methods and a summary of their specific context of the measurement using, nursing institution in Shanghai, China are regarded as a typical case to practice these methods and compare the differences in using. Meantime, the impact of the politics and planning related to this special facility is also been considered. Results show that, accessibility of nursing institution among elderly groups is much different under different research distance, and the overall trend seems like the research units in suburb appears higher accessibility than those in highly urbanized area. And Gink Coefficient helps us determine the proportion of the elderly population in different reachable areas in Shanghai is within a reasonable range. However, Global Moran’ index provide reliable evidence that the existence of the aggregation combined by the high-value units. It indicates that there are inequities among the distribution of aged-nursing resources, and Local Moran I （LISA）help us to find the specific boundaries of these areas. In general, in the study of the equity related to location, accessibility can only reflect the differences phenomenon in distribution, but it is not clear to describe this gap to what extent, and it’s difficult to achieve the possibility of comparison among different periods and different subjects. The Gini coefficient often focuses on the unfairness of the distribution of people, but ignored the aggregation characteristics of the spatial dimension, which the analysis of spatial autocorrelation can make up. All these methods proved that it’s necessary to consider both the spatial distribution of supply and demand. And the discussion about equity related to location should be strictly qualified in study.

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Unraveling the COVID-19 hospitalization dynamics in Spain using publicly available data

10.1101/2021.09.03.21263086 ◽

2021 ◽

Author(s):

Alberto Aleta ◽

Juan Luis Blas-Laína ◽

Gabriel Tirado Anglés ◽

Yamir Moreno

Keyword(s):

Economic Status ◽

Healthcare Services ◽

Model Parameters ◽

Health Authorities ◽

Infection Dynamics ◽

Bayesian Inference Method ◽

Different Populations ◽

Autonomous Regions ◽

The Impact

SummaryBackgroundOne of the main challenges of the ongoing COVID-19 pandemic is to be able to make sense of available, but often heterogeneous and noisy data, to characterize the evolution of the SARS-CoV-2 infection dynamics, with the additional goal of having better preparedness and planning of healthcare services. This contribution presents a data-driven methodology that allows exploring the hospitalization dynamics of COVID-19, exemplified with a study of 17 autonomous regions in Spain.MethodsWe use data on new daily cases and hospitalizations reported by the Ministry of Health of Spain to implement a Bayesian inference method that allows making short and mid-term predictions of bed occupancy of COVID-19 patients in each of the autonomous regions of the country.FindingsWe show how to use given and generated temporal series for the number of daily admissions and discharges from hospital to reproduce the hospitalization dynamics of COVID-19 patients. For the case-study of the region of Aragon, we estimate that the probability of being admitted to hospital care upon infection is 0·090 [0·086-0·094], (95% C.I.), with the distribution governing hospital admission yielding a median interval of 3·5 days and an IQR of 7 days. Likewise, the distribution on the length of stay produces estimates of 12 days for the median and 10 days for the IQR. A comparison between model parameters for the regions analyzed allows to detect differences and changes in policies of the health authorities.InterpretationThe amount of data that is currently available is limited, and sometimes unreliable, hindering our understanding of many aspects of this pandemic. We have observed important regional differences, signaling that to properly compare very different populations, it is paramount to acknowledge all the diversity in terms of culture, socio-economic status and resource availability. To better understand the impact of this pandemic, much more data, disaggregated and properly annotated, should be made available.

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Anticipation Mechanism for Cold Wave: Forecast Based Financing a Case Study in the Peruvian Andes

Frontiers in Climate ◽

10.3389/fclim.2021.747906 ◽

2021 ◽

Vol 3 ◽

Author(s):

Juan Bazo ◽

Coughlan de Perez ◽

Gerardo Jacome ◽

Kemper Mantilla ◽

Mathieu Destrooper ◽

...

Keyword(s):

Household Survey ◽

The Elderly ◽

Red Cross ◽

Cold Wave ◽

Peruvian Andes ◽

Household Level ◽

Early Action ◽

Wave Forecast ◽

The Impact

In June 2018, the Peruvian provinces of Arequipa and Puno in the southern Andean region were affected by heavy snowfall, which caused severe damage to people and livelihoods in several communities. Using the Forecast-based Financing approach, the Peruvian Red Cross implemented its pre-defined early action protocol before this event, after receiving an extreme snowfall warning (Level 4) from the Peruvian meteorological service. Here, we provide a case study of the approach and event itself, documenting the decision-making thresholds as well as the actions taken. This warning activated the thresholds established in the protocol, and Peruvian Red Cross prioritized 10 communities for pre-disaster support based on the forecasted severity of the event in combination with vulnerability and exposure information. The activation took place 2 days before the extreme snowfall in the communities, and the Red Cross distributed veterinary kits for 50 heads of cattle per family, tarpaulins, tool kits to install a temporary awning for alpacas to protect them from the cold wind and snow, protection kits for alpaca herders and warm clothing for children under five, pregnant women, the elderly, and people with chronic and infectious diseases in 430 highly vulnerable households. This article presents the results of a household survey following the impact of the extreme snowfall. We document the early actions taken by these communities to protect their livelihoods, health, and assets. The evaluation also presents descriptive statistics of household-level outcomes for households receiving pre-snowfall support and those that did not receive any intervention or only received post-disaster assistance. While most households took action to protect their assets, there were fewer extreme losses of alpaca herds reported in the communities who received the early support, and these communities also reported fewer adults suffering from respiratory illnesses. More in-depth research on this type of early action is necessary on a wider scale, especially to evaluate the utility of different support measures and the necessary quantity of support needed. This case study can inform government, civil society, and humanitarian actors of how early action is happening before disasters occur and provide a direction for further investment in research and practice to make use of hydro-meteorological forecasts for the benefit of the most vulnerable.

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