Introduction of Covid 19 and Contextual Analysis

Covid-19 has forced many families and businesses to put their everyday practices on hold. Even with many restrictions being lifted and a sense of normalcy finally befalling society, the coming winter season estimates another COVID surge underway. All around California, rates are steadily increasing with L.A. County figures rising to a level where indoor masks might be mandated again (Kawahara et al., 2022). A recent CDC report found that 41.6% of adults have SARS-CoV-2 anti-N antibodies which are often correlated to the previous infection. However, the concern is that out of the 655 participants with anti-S-positive and anti-N-positive results self-reported that they never experienced COVID-19 (Akinbami et al., 2022). Even though these are based on self-reported data, the concern for asymptomatic spreading resulting in additional cases is a public health concern. With the declining administering of the bi-valent booster, with only 7% of 209 million eligible individuals receiving their dosage, concern for future preparedness is being acknowledged (Vaziri, 2022).

Case Study of Covid-19 Cases concerning Health & Disadvantaged Communities

For the current study, Covid-19 cases were compared to two variables…

  1. Reported Cardiovascular Cases
  2. Disadvantaged Communities (Poverty %, Median Household Income (MHI), etc.)

Both of these variables were the focus of the spatial study. These were chosen due to Covid-19 being a virus that has mainly targeted a human’s cardiovascular system as well as the overlay of poverty indexes to see if there is a possible correlation. The goal is to figure out if Covid-19 cases and their associated health concerns have a distinct spatial correlation with disadvantaged communities.

People with primary Covid-19 hospitalizations were found to experience an increased risk for venous thromboembolism (VTE) heart failure, and stroke with secondary cardiovascular risks showing similar increases as well (Raisi-Estabragh et al., 2022). The increase in the number of diseases and mortality outcomes poses significant health problems even after returning to healthy levels. Another study conducted found that acute COVID-19 individuals that didn’t require hospitalization also showed increased cardiovascular diseases such as ischemic and non-ischemic heart disease (Xie et al., 2022). Long-term care and monitoring for these factors aren’t always plausible for people with busy schedules as well as being cost-efficient.

The second selection of income and poverty are also chosen for this study. These are based on qualities found in disadvantaged communities. According to the California Public Utilities Commission, disadvantaged communities include economic, health, and environmental burdens (poverty, unemployment, etc.) (CPUC, 2021). Past research has also compared income and race with Covid-19 mortality rates. One study was based on income gradient contributions to Covid-19 rates and morbidity. It was based in Mexico and some of the findings found probabilities for hospitalization to be four times higher in lower-income families versus richer individuals (Arceo-Gomez et al., 2021). However, the difference between dying while being categorized as a rich or poor individual was equal to being a person who is immunosuppressed or twice the chances of having diabetes which is prevalent in the current population. This brings into question the correlation between selected variables and wide-scale generalization.

Covid Cases in California

Under these two conditions, the deployment of these factors was conducted through geospatial analysis. Utilizing CalEnviroScreen, census tract data, and Covid-19 case data in the US, analysis of these conditions on top of each other allowed spatial comparison of these variables. Some additional layers such as Disadvantaged communities as well as Tiger/Line shapefiles allowed county borders as well as applicable MHI values to be included in the mapping process.

Figure 1. California Covid Cases by County

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