Analyze

the floor of the valley has dropped in recent decades with increased groundwater pumping by farms, meaning more land might be subject to inundation,

Flood protection in California is largely a local affair, with water agencies, special districts and private companies building and maintaining the infrastructure. Smaller towns, like those in the San Joaquin Valley, often don’t have the money to develop their own levee systems, and while the state and federal government help out, winning investment from them isn’t easy.

The Tulare Lake basin also doesn’t have major Army Corps of Engineers flood projects to buffer large amounts of water as do some areas such as the Sacramento region.

The current crisis is the opposite of the usual one--instead of fighting over who gets access to water, groups are fighting over how to get rid of it.

Farmers, residents, municipal work crews, and hired contractors are reinforcing levees, pumping out excess water, and evacuating livestock, equipment, and homes.

One group was hired to protect a supply warehouse 3 miles south of Corcoran.

J.G. Boswell Company, which mainly produces cotton, owns most of the lowlands that are the Tulare Lake bed. They have allowed some fields to flood in efforts to protect other areas (the most productive farmland). The County Board of Supervisors forced them to cut another levee and flood more land because they weren't doing enough to protect populated areas.

"Flood protection in California is largely a local affair, with water agencies, special districts and private companies building and maintaining the infrastructure. Smaller towns, like those in the San Joaquin Valley, often don’t have the money to develop their own levee systems, and while the state and federal government help out, winning investment from them isn’t easy. The Tulare Lake basin also doesn’t have major Army Corps of Engineers flood projects to buffer large amounts of water as do some areas such as the Sacramento region."

Tulare lake used to be the largest body of water east of the Mississipppi. It had ports, steamships, elk and antelope. 40 different Yokut groups lived on its shores.

The Covid-19 Pandemic Vulnerability Index (PVI) Dashboard, which relies on the Toxicological Prioritization Index (ToxiPi) to integrate diverse data into a geospatial context.

National Institute of Environmental Health Sciences (NIEHS). COVID-19 Pandemic Vulnerability Index (PVI) Dashboard. 2021. Available online: https://covid19pvi.niehs.nih.gov/ (accessed on 24 July 2021).

The PVI dashboard is included in the CDCD’s Covid-19 Data Tracker as part of the “Unique Populations” tab.  

NIEHS also developed Covid-19 PVI lesson plans for high school students (grades 9 – 12) to learn to examine risk factors associated with Covid-19 using the index. The goals of the curriculum are to provide students with a tool for examining the spread and health outcomes of a pandemic, to promote their awareness of how various factors (biological, social, behavioral, etc.) impact disease spread and outcomes, and to support the development of prevention and intervention strategies that reduce exposures to risk factors and their adverse health impacts. The lesson plans highlight the significance of social and environmental determinants in public health.

Learning objectives of the curriculum include:

• Knowing what a mathematical model is, the purpose of using a mathematical model
• How to examine the social factors contributing to the spread of infectious disease
• How to analyze the environmental factors that contribute to the spread of infectious disease
• Knowing about intervention strategies that could mitigate the impact of infectious disease on public health

The PVI dashboard was also used by anthropologist Jayajit Chakraborty to examine the relationship between Covid-19 vulnerability and disability status in the US. Chakraborty applied the dashboard and data from the 2019 American Community Survey to investigate whether vulnerability to the pandemic has been significantly greater in counties containing higher percentages of people with disabilities in four timeframes from May 2020 to February 2021. Chakraborty found that the percentage of people with disabilities (as well as those reporting other cognitive, vision, ambulatory, self-care and independent living difficulties) was significantly greater in counties with the highest 20% of the PVI. Chakraborty calls for further research to better understand the adverse impacts of Covid-19 on PwDs (people with disabilities).

Chakraborty, J. Vulnerability to the COVID-19 Pandemic for People with Disabilities in the U.S. Disabilities 2021, 1, 278-285. https://doi.org/10.3390/disabilities1030020

The index produces an overall score derived from 12 indicators distributed across four domains (current infection rates, baseline population concentration, current interventions, and health and environmental vulnerabilities. Each vulnerability factor is represented as a slide of a radar chart (see below).

The dashboard can also be used to visualize changes over time in cases, deaths, PVI, and PVI rank (with a line chart and a bar chart), as well as predicted changes in cases and deaths (with a line chart), see below.

Additional visual layers can be added to the PVI map (e.g. number of cases and deaths).

The PVI offers a visual synthesis of information to monitor disease trajectories, identify local vulnerabilities, forecast outcomes, and guide an informed response (e.g. allocating resources). This includes short-term, local predictions of cases and deaths. The PVI dashboard creates profiles (called PVI scorecards) for every county in the United States.

The PVI dashboard can be customized to specific needs by adding or removing layers of information, filtering by region, or clustering by profile similarity. The Predictions panel connects historical tracking to local forecasts of cases and deaths. The dashboard applies an integrated concept of vulnerability composed of both dynamic (infection rate and interventions) and static (community population and health care access) factors.

The statistical modeling supporting the PVI dashboard (generalized linear models of cumulative outcome data) has indicated that following population size, the most significant predictors of cases and deaths were the proportion of Black residents, mean fine particulate matter [particulate matter ≤2.5μm in diameter (PM2.5)], percentage of population with insurance coverage, and proportion of Hispanic residents.

The ToxPi*GIS framework, from which the PVI was built, is a free tool that integrates data streams from different sources into interactive profiles that overlay geographic information systems (GIS) data. This enables people using the tool to compare, cluster, and evaluate the sensitivity of a statistical framework to component data streams. In other words, this enables the integration of data that are not normally compared (data are combined into a matrix comprised of various domains or categories, varying weights and represented by color schemes).