diff --git a/src/assets/text/text_en.js b/src/assets/text/text_en.js
index 3c16aad6eec5cbf57d5da33256fb4f9a0ab21127..b0b28ed10afa26a272fb1702eaca47e5484bd70c 100644
--- a/src/assets/text/text_en.js
+++ b/src/assets/text/text_en.js
@@ -11,19 +11,19 @@ export default {
mapText: {
title: "Vulnerability indicators across the Western states ",
p1Title: "Household sizes",
- paragraph1: "Infrastructure and institutional factors are major determinants of access to and reliability of water delivery in the United States <a href='https://doi.org/10.1029/2023WR036284' target='_blank'>(Drakes and others, 2024)</a>. <a href='https://wires.onlinelibrary.wiley.com/doi/10.1002/wat2.1486' target='_blank'>Meehan and others (2020)</a> found 471,000 households or 1.1 million people lacked piped water access between 2013 and 2017, with the majority (73%) of these households located in metropolitan areas, and nearly half (47%) in the 50 largest urban areas. The reviewed literature showed indicators of household size, female-headed households, female population, and percentage of females in the labor force were all predominantly positively related and influential to water insecurity conditions. Displayed below is a county-level map of the average household size of occupied housing units. Counties with the greatest average household size, shown in dark blue, include Oglala Lakota County, South Dakota; Madison County, Idaho; and Todd County, South Dakota.",
+ paragraph1: "Infrastructure and institutional factors are major determinants of access to and reliability of water delivery in the United States <a href='https://doi.org/10.1029/2023WR036284' target='_blank'>(Drakes et al, 2024)</a>. <a href='https://wires.onlinelibrary.wiley.com/doi/10.1002/wat2.1486' target='_blank'>Meehan et al (2020)</a> found 471,000 households or 1.1 million people lacked piped water access between 2013 and 2017, with the majority (73%) of these households located in metropolitan areas, and nearly half (47%) in the 50 largest urban areas. The reviewed literature showed indicators of household size, female-headed households, female population, and percentage of females in the labor force were all predominantly positively related and influential to water insecurity conditions. Displayed below is a county-level map of the average household size of occupied housing units. Counties with the greatest average household size, shown in dark blue, include Oglala Lakota County, South Dakota; Madison County, Idaho; and Todd County, South Dakota.",
caption1: `<span class="tooltip-group"><span class="tooltip-span">Choropleth map</span><span id="choropleth-map-tooltip" class="tooltiptext">Type of map that displays divided geographical areas or regions that are coloured, shaded or patterned in relation to a data variable. This provides a way to visualise values over a geographical area, which can show variation or patterns across the displayed location.</span></span> of average household size, of occupied housing units, at the county-level across the contiguous U.S.. The greatest average housing size were in Oglala Lakota County, South Dakota (5), Madison County, Idaho (3.9) and Todd County, South Dakota (3.8) <a href='https://www.census.gov/data/developers/data-sets/acs-5year.html' target='_blank'>(U.S. Census Bureau, 2022).</a>`,
p2Title: "Income inequalities",
- paragraph2: "Low income and impoverished persons are more likely to experience conditions associated with water insecurity. Moreover, income inequality is a highly significant predictor of 'plumbing poverty,' meaning homes that lack complete indoor plumbing <a href='https://www.pnas.org/doi/abs/10.1073/pnas.2007361117' target='_blank'>(Meehan and others, 2020)</a>. The county-level map below displays median household income in the past 12 months (in 2022 inflation-adjusted dollars). Counties with the greatest median household income are shown in dark blue and include Santa Clara County, California; San Mateo County, California; and Marin County, California.",
+ paragraph2: "Low income and impoverished persons are more likely to experience conditions associated with water insecurity. Moreover, income inequality is a highly significant predictor of 'plumbing poverty,' meaning homes that lack complete indoor plumbing <a href='https://www.pnas.org/doi/abs/10.1073/pnas.2007361117' target='_blank'>(Meehan et al, 2020)</a>. The county-level map below displays median household income in the past 12 months (in 2022 inflation-adjusted dollars). Counties with the greatest median household income are shown in dark blue and include Santa Clara County, California; San Mateo County, California; and Marin County, California.",
caption2: `Choropleth map of median household income in the past 12 months (in 2022 inflation-adjusted dollars) at the county-level across the contiguous U.S.. The greatest median incomes include Santa Clara County, California ($153,792), San Mateo County, California ($149,907) and Marin County, California ($142,019) <a href='https://www.census.gov/data/developers/data-sets/acs-5year.html' target='_blank'>(U.S. Census Bureau, 2022).</a>`,
p3Title: "Renter disparities",
- paragraph3: "As median rent values go up, water insecurity tends to go down, likely reflecting greater access to resources for wealthier populations <a href='https://www.sciencebase.gov/catalog/item/63f79d49d34e4f7eda456572' target='_blank'>(Hines and others, 2023)</a>. That said, renters tend to be at a higher risk of losses from water-related hazards compared to homeowners. After disasters, renters are more likely to relocate and less likely to apply for and receive assistance. Renters also often lack the authority and means to enact structural changes to their homes for hazard mitigation, response, or recovery, which raises the hazard exposure and susceptibility of renters while lowering their capacity to cope <a href='https://doi.org/10.1016/j.ijdrr.2020.102010' target='_blank'>(Drakes and others, 2021) </a>. The county-level map below displays median gross rent. Counties with the greatest median gross rent, shown in dark green, include San Mateo County, California; Santa Clara County, California; and Marin County, California.",
+ paragraph3: "As median rent values go up, water insecurity tends to go down, likely reflecting greater access to resources for wealthier populations <a href='https://www.sciencebase.gov/catalog/item/63f79d49d34e4f7eda456572' target='_blank'>(Hines et al, 2023)</a>. That said, renters tend to be at a higher risk of losses from water-related hazards compared to homeowners. After disasters, renters are more likely to relocate and less likely to apply for and receive assistance. Renters also often lack the authority and means to enact structural changes to their homes for hazard mitigation, response, or recovery, which raises the hazard exposure and susceptibility of renters while lowering their capacity to cope <a href='https://doi.org/10.1016/j.ijdrr.2020.102010' target='_blank'>(Drakes et al, 2021) </a>. The county-level map below displays median gross rent. Counties with the greatest median gross rent, shown in dark green, include San Mateo County, California; Santa Clara County, California; and Marin County, California.",
caption3: `Choropleth map of median gross rent at the county-level across the contiguous U.S.. The greatest median gross rents include San Mateo County, California ($2,805), Santa Clara County, California ($2,719) and Marin County, California ($2,487) <a href='https://www.census.gov/data/developers/data-sets/acs-5year.html' target='_blank'>(U.S. Census Bureau, 2022).</a>`,
p4Title: "Hispanic populations",
- paragraph4: "Hispanic populations are at an increased risk of water insecurity <a href='https://www.sciencebase.gov/catalog/item/63f79d49d34e4f7eda456572' target='_blank'>(Hines and others, 2023)</a>. In some areas of the country, Hispanic households are more likely to experience 'plumbing poverty'—meaning homes that lack complete indoor plumbing <a href='https://www.pnas.org/doi/abs/10.1073/pnas.2007361117' target='_blank'>(Meehan and others, 2020)</a>—particularly in the Western United States. In fact, research shows that although Hispanic-headed households make up less than 13% of all U.S. households, they account for nearly 17% of households with incomplete plumbing <a href='https://doi.org/10.1080/24694452.2018.1530587' target='_blank'>(Deitz & Meehan, 2019)</a>. The county map below shows the percent of Hispanic populations. Counties with the greatest percent of Hispanic residents, shown in dark blue, include Kenedy County, Texas; Starr County, Texas; and Webb County, Texas. These areas are particularly affected by the combined challenges of water insecurity and plumbing poverty.",
+ paragraph4: "Hispanic populations are at an increased risk of water insecurity <a href='https://www.sciencebase.gov/catalog/item/63f79d49d34e4f7eda456572' target='_blank'>(Hines et al, 2023)</a>. In some areas of the country, Hispanic households are more likely to experience 'plumbing poverty'—meaning homes that lack complete indoor plumbing <a href='https://www.pnas.org/doi/abs/10.1073/pnas.2007361117' target='_blank'>(Meehan et al, 2020)</a>—particularly in the Western United States. In fact, research shows that although Hispanic-headed households make up less than 13% of all U.S. households, they account for nearly 17% of households with incomplete plumbing <a href='https://doi.org/10.1080/24694452.2018.1530587' target='_blank'>(Deitz & Meehan, 2019)</a>. The county map below shows the percent of Hispanic populations. Counties with the greatest percent of Hispanic residents, shown in dark blue, include Kenedy County, Texas; Starr County, Texas; and Webb County, Texas. These areas are particularly affected by the combined challenges of water insecurity and plumbing poverty.",
caption4: `Choropleth map of percent of Hispanic populations at the county-level across the contiguous U.S.. The greatest percent Hispanic were in Kenedy County, Texas (96.6%), Starr County, Texas (96.2%) and Webb County, Texas (95.4%) <a href='https://www.census.gov/data/developers/data-sets/acs-5year.html' target='_blank'>(U.S. Census Bureau, 2022).</a>`,
p5Title: "Disabled populations",
- paragraph5: "Special needs and disabled populations may live in places more exposed to water-related hazards <a href='https://www.sciencedirect.com/science/article/abs/pii/S0277953619301121' target='_blank'>(Chakraborty and others, 2019)</a> or experiencing unreliable or intermittent potable water supplies <a href='https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155043' target='_blank'>(White and others, 2016)</a>. For example, <a href='https://doi.org/10.1029/2023WR036284' target='_blank'>Drakes and others (2024)</a> found special needs and disabled populations were associated with a higher likelihood of water insecure conditions in the Western United States. However, only two studies have measured the relationship between disability and water insecurity, and the limited research on the topic was conducted only in the municipal water-use sector. The map below shows the percent of disabled persons in each county. Counties with the greatest percent of disabled individuals, shown in dark blue, include Catron County, New Mexico; Mora County, New Mexico; and Kinney County, Texas.",
+ paragraph5: "Special needs and disabled populations may live in places more exposed to water-related hazards <a href='https://www.sciencedirect.com/science/article/abs/pii/S0277953619301121' target='_blank'>(Chakraborty et al, 2019)</a> or experiencing unreliable or intermittent potable water supplies <a href='https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155043' target='_blank'>(White et al, 2016)</a>. For example, <a href='https://doi.org/10.1029/2023WR036284' target='_blank'>Drakes et al (2024)</a> found special needs and disabled populations were associated with a higher likelihood of water insecure conditions in the Western United States. However, only two studies have measured the relationship between disability and water insecurity, and the limited research on the topic was conducted only in the municipal water-use sector. The map below shows the percent of disabled persons in each county. Counties with the greatest percent of disabled individuals, shown in dark blue, include Catron County, New Mexico; Mora County, New Mexico; and Kinney County, Texas.",
caption5: `Choropleth map of percent with a disability of total civilian noninstitutionalized population at the county-level across the contiguous U.S.. The greatest percent disabled were in Catron County, New Mexico (41%), Mora County, New Mexico (34%) and Kinney County, Texas (34%) <a href='https://www.census.gov/data/developers/data-sets/acs-5year.html' target='_blank'>(U.S. Census Bureau, 2022).</a>`,
},
metaAnalysisText: {
@@ -43,7 +43,7 @@ export default {
},
chartText: {
bubbleText: "Interact with the chart to explore evidence<br>for social vulnerability determinants.",
- bubbleLegend: `Many social vulnerability determinants have been studied. Some show positive <span class="legend-box positive"></span> relationships with water insecurity, some negative <span class="legend-box negative"></span>, and others unknown <span class="legend-box unknown"></span> <a href='https://www.sciencebase.gov/catalog/item/63f79d49d34e4f7eda456572' target='_blank'>(Hines and others, 2023)</a>`,
+ bubbleLegend: `Many social vulnerability determinants have been studied. Some show positive <span class="legend-box positive"></span> relationships with water insecurity, some negative <span class="legend-box negative"></span>, and others unknown <span class="legend-box unknown"></span> <a href='https://www.sciencebase.gov/catalog/item/63f79d49d34e4f7eda456572' target='_blank'>(Hines et al, 2023)</a>`,
bubbleYaxis: `The y-axis of the chart represents the level of agreement among studies where increased <b>consensus</b> indicates a majority of studies using the selected determinant recorded the same direction of influence on conditions of water insecurity and <b>inconclusive</b> indicates studies using the selected determinant did not record the same direction of influence on conditions of water insecurity. The size of the bubbles on the chart represents the number of studies, with larger bubbles indicating that a particular determinant has been studied more frequently.`,
bubbleCheckbox: `Everyone needs access to clean water. For those with limited access, <span class="tooltip-group"><span class="tooltip-span"> water insecurity </span><span id="water-insecurity-tooltip" class="tooltiptext"> Populations cannot maintain access to adequate quantities of water at an acceptable quality to sustain livelihoods, development, and human and ecosystem health.</span></span> has a daily impact on their lives. People may be more or less vulnerable to water insecurity due to`,
bubbleLabels: {