The population density of Berkeley County, WV was 353 in 2018.
Population Density
Population Density is computed by dividing the total population by Land Area Per Square Mile.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Geographic and Population Datasets Involving Berkeley County, WV
- API
NCHS - Drug Poisoning Mortality by County: United States
data.cdc.gov | Last Updated 2022-03-30T13:15:49.000ZThis dataset describes drug poisoning deaths at the county level by selected demographic characteristics and includes age-adjusted death rates for drug poisoning from 1999 to 2015. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2015 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Estimate does not meet standards of reliability or precision. Death rates are flagged as “Unreliable” in the chart when the rate is calculated with a numerator of 20 or less. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Estimates should be interpreted with caution. Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year during 1999–2015. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates are unavailable for Broomfield County, Colo., and Denali County, Alaska, before 2003 (6,7). Additionally, Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. County boundaries are consistent with the vintage 2005-2007 bridged-race population file geographies (6).
- API
NCHS - Drug Poisoning Mortality by County: United States
data.cdc.gov | Last Updated 2022-03-29T21:27:25.000ZThis dataset contains model-based county estimates for drug-poisoning mortality. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2016 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances. Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates for 1999-2015 have been updated, and may differ slightly from previously published estimates. Differences are expected to be minimal, and may result from different county boundaries used in this release (see below) and from the inclusion of an additional year of data. Previously published estimates can be found here for comparison.(6) Estimates are unavailable for Broomfield County, Colorado, and Denali County, Alaska, before 2003 (7,8). Additionally, Clifton Forge County, Virginia only appears on the mortality files prior to 2003, while Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. These counties were therefore merged with adjacent counties where necessary to create a consistent set of geographic units across the time period. County boundaries are largely consistent with the vintage 2005-2007 bridged-race population file geographies, with the modifications noted previously (7,8). REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm. 2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html. 3. Rossen LM, Khan D, Warner M. Trends and geographic patterns in drug-poisoning death rates in the U.S., 1999–2009. Am J Prev Med 45(6):e19–25. 2013. 4. Rossen LM, Khan D, Warner M. Hot spots in mortality from drug poisoning in the United States, 2007–2009. Health Place 26:14–20. 2014. 5. Rossen LM, Khan D, Hamilton B, Warner M. Spatiotemporal variation in selected health outcomes from the National Vital Statistics System. Presented at: 2015 National Conference on Health Statistics, August 25, 2015, Bethesda, MD. Available from: http://www.cdc.gov/nchs/ppt/nchs2015/Rossen_Tuesday_WhiteOak_BB3.pdf. 6. Rossen LM, Bastian B, Warner M, and Khan D. NCHS – Drug Poisoning Mortality by County: United States, 1999-2015. Available from: https://data.cdc.gov/NCHS/NCHS-Drug-Poisoning-Mortality-by-County-United-Sta/pbkm-d27e. 7. National Center for Health Statistics. County geog
- API
NCHS - Drug Poisoning Mortality by State: United States
data.cdc.gov | Last Updated 2022-03-28T19:47:01.000ZThis dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning from 1999 to 2015. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2015 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Estimate does not meet standards of reliability or precision. Death rates are flagged as “Unreliable” in the chart when the rate is calculated with a numerator of 20 or less. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Estimates should be interpreted with caution. Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year during 1999–2015. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates are unavailable for Broomfield County, Colo., and Denali County, Alaska, before 2003 (6,7). Additionally, Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. County boundaries are consistent with the vintage 2005-2007 bridged-race population file geographies (6).
- API
NCHS - Drug Poisoning Mortality by County: United States
data.cdc.gov | Last Updated 2023-04-20T17:42:22.000ZThis dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances. REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm. 2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.
- API
Incidence Rate Of Leukemia Per 100,000 All States
opendata.utah.gov | Last Updated 2019-04-19T00:30:16.000ZIncidence Rate Of Leukemia Per 100,000 All States
- API
Incidence Of Brain And Central Nervous System Cancer Age 15 Under Per 1,000,000 All States
opendata.utah.gov | Last Updated 2019-04-19T01:42:51.000ZIncidence Of Brain And Central Nervous System Cancer Age 15 Under Per 1,000,000 All States
- API
Vital Signs: Population – by city (2022)
data.bayareametro.gov | Last Updated 2023-06-20T23:39:39.000ZVITAL SIGNS INDICATOR Population (LU1) FULL MEASURE NAME Population estimates LAST UPDATED February 2023 DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region. DATA SOURCE California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ Table E-6: County Population Estimates (1960-1970) Table E-4: Population Estimates for Counties and State (1970-2021) Table E-8: Historical Population and Housing Estimates (1990-2010) Table E-5: Population and Housing Estimates (2010-2021) Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs Computed using 2020 US Census TIGER boundaries U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University 1970-2020 U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/ 2011-2021 Form B01003 Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022. Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator. Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs). The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and
- API
Vital Signs: Population – by PDA (2022)
data.bayareametro.gov | Last Updated 2023-06-20T23:39:41.000ZVITAL SIGNS INDICATOR Population (LU1) FULL MEASURE NAME Population estimates LAST UPDATED February 2023 DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region. DATA SOURCE California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ Table E-6: County Population Estimates (1960-1970) Table E-4: Population Estimates for Counties and State (1970-2021) Table E-8: Historical Population and Housing Estimates (1990-2010) Table E-5: Population and Housing Estimates (2010-2021) Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs Computed using 2020 US Census TIGER boundaries U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University 1970-2020 U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/ 2011-2021 Form B01003 Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022. Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator. Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs). The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and
- API
Vital Signs: Population – by tract (2022)
data.bayareametro.gov | Last Updated 2023-06-20T23:39:40.000ZVITAL SIGNS INDICATOR Population (LU1) FULL MEASURE NAME Population estimates LAST UPDATED February 2023 DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region. DATA SOURCE California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ Table E-6: County Population Estimates (1960-1970) Table E-4: Population Estimates for Counties and State (1970-2021) Table E-8: Historical Population and Housing Estimates (1990-2010) Table E-5: Population and Housing Estimates (2010-2021) Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs Computed using 2020 US Census TIGER boundaries U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University 1970-2020 U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/ 2011-2021 Form B01003 Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022. Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator. Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs). The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and
- API
Vital Signs: Population – Bay Area (2022)
data.bayareametro.gov | Last Updated 2023-06-20T23:39:36.000ZVITAL SIGNS INDICATOR Population (LU1) FULL MEASURE NAME Population estimates LAST UPDATED February 2023 DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region. DATA SOURCE California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ Table E-6: County Population Estimates (1960-1970) Table E-4: Population Estimates for Counties and State (1970-2021) Table E-8: Historical Population and Housing Estimates (1990-2010) Table E-5: Population and Housing Estimates (2010-2021) Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs Computed using 2020 US Census TIGER boundaries U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University 1970-2020 U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/ 2011-2021 Form B01003 Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022. Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator. Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs). The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and