Earthquake and Floods, California, U.S. | January 2023

January 9, 2023 | Santa Barbara – Ventura, Southern California, United States

This report provides information on population density changes, baseline population vulnerabilities, and bed capacities at local healthcare facilities between Santa Barbara and Ventura, California. Data provided in this report were updated on January 10, 2023.

Key Observations:

  • Despite heavy flooding as of January 9, 2023, the areas between Santa Barbara and Ventura saw minimal changes in population densities and movement.
  • There were two significant exceptions to this trend: Montecito saw a decline in population density of 22% and the campus of the University of California Santa Barbara (UCSB) saw an increased density of 22%.

January 9, 2023 | Santa Cruz – Monterey, Northern California, United States

This report provides information on population density changes, baseline population vulnerabilities, and bed capacities at local healthcare facilities between Santa Cruz and Monterey, California. Data provided in this report were updated on January 10, 2023. In California, Santa Cruz and Monterey were among the most-affected areas by recent floods.

Key Observations:

  • Relatively low levels of population movement were detected in Santa Cruz and Monterey at the time of analysis.
  • Among higher population areas, Monterey exhibited a population decline of 8%, and Salinas a decline by 9%.
  • It is likely that low levels of movement are attributed to transportation impairment from flooded roads and other obstructions.

January 5, 2023 | Northern California, United States

This report provides information on population density changes in the northern California counties affected by a 5.4 magnitude earthquake, which struck the region on January 1, 2023. Subsequent flooding caused by heavy rainfall and strong wind has exacerbated displacement throughout northern California, especially Sacramento and the San Francisco Bay Area.

Key Observations:

  • Population densities remain above baseline values in pockets of Humboldt County at the time of analysis.
  • Declines in population densities since the peak of holiday travel can be detected across multiple surrounding counties, including Placer, Yuba, and Butte Counties.
  • Since the earthquake struck, the most significant declines in population have been in Trinity County.
  • The risk of power outages, floods, and further displacement is expected to increase as multiple cyclones make their way from the Pacific Ocean toward California.

Earthquake in West Java, Indonesia | November 2022

November 21, 2022 | West Java, Indonesia
This report provides information on population density changes in the district of Cianjur in West Java, Indonesia after the region was struck by a 5.7 magnitude earthquake.

Key Observations:

  • As of November 22, 2022, official totals indicated the earthquake caused 268 deaths, over 500 injuries, and nearly 60,000 people to be displaced.
  • The Cianjur district experienced a dramatic, short-term population decrease, which quickly turned towards a significant increase at the time of analysis.
  • Shortly after the earthquake struck the region, the recorded population decreased 38% in Cianjur, and then increased by 12% 16 hours later.
  • The initial decrease in Cianjur totaled to over 33,000 individuals, which then shifted to an increase of more than 20,000.

November 21, 2022 | West Java, Indonesia
This report provides insights on population movement dynamics after the earthquake struck West Java, Indonesia.

Key Observations:

  • At the time of analysis, residents who were located near the center of the earthquake moved towards the coastal area in the south and to the areas northeast of the earthquake.
  • Naringgul, Tegal Buleud, Agrabinta, Cikalongkulon, Cikadu, Cihurip, and Bojonggambir all had population increases of 15% or higher.

Cyclone Sitrang, Bangladesh | October 2022

October 30, 2022 | Bangladesh (Nation-Wide)
This report provides information on population density changes as of October 30, 2022, in the areas of Bangladesh most affected by the Sitrang Cyclone, which made landfall in the country on October 25, 2022.

Key Observations:

  • Roughly one week since Cyclone Sitrang struck Bangladesh, population density levels across the country have returned to pre-crisis levels.
  • No district in the country is below a 4% change, relative to baseline population values.
  • On average, return to baseline population density values took -3 days.
  • Concerns are still running high among health officials in Bangladesh. They worry that standing water may increase mosquito breeding in the 10-14 day window post-storm, resulting in increasing vector disease cases, particularly dengue.

October 28, 2022 | Southern Bangladesh
This report provides information on population movement dynamics using data collected between October 25, when the Sitrang Cyclone first made landfall, to October 28, 2022.

Key Observations:

  • Population densities at the period of analysis show that the areas most affected by the cyclone have returned to the pre-event levels.
  • Three level 2 units have a trackable population slightly below the pre-event condition (b/w 6 to 15% lower than pre-event)

October 27, 2022 | Southern Bangladesh
This report provides information on population movement dynamics using data collected between October 25, when the Sitrang Cyclone first broke out, to October 27, 2022.

Key Observations:

  • Population densities in the affected areas are gradually returning to pre-event levels.
  • Chandpur is the only level 2admin unit with a trackable population below pre-event by 15% or greater

October 26, 2022 | Southern Bangladesh
This report provides information on population movement dynamics since Cyclone Sitrang made lanfall in southern Bangladesh on Tuesday, October 25, 2022.

Key Observations:

  • Mobility data from October 26, 2022 (and updated on October 27, 2022) indicates an extremely rapid mass evacuation and then return to areas affected by the cyclone.
  • Areas throughout the Eastern districts of Bangladesh saw population declines on October 25th and 26th ranging from -70% to -30% in the most affected regions. However, by the end of October 26, these districts had mostly returned to baseline population values.
  • The populations of the Noakhali, Gopalganj, Munshiganj, Shariatpur, Lakshmipur, and Chandpur districts remained below baseline values at rates between -9% and -19%.

October 25, 2022 | Southern Bangladesh

This one-page report provides an overview of population movement patterns after Cyclone Sitrang made landfall on October 25, 2022. The percent changes included in this report are relative to number of Facebook users detected.

Key Observations:

  • The Southern regions of Bangladesh were most affected by the landfall of the cyclone.
  • Level-2 administrative units with the greatest population displacement include: Lakshipur, Chandpur, Munshiganj, Shariatpur, Noakhali, and Gopalganj.
  • Lakshmipur, Chandpur, and Munshiganj saw the most significant declines in population densities, with averages between -36% and -54%.

Tropical Storm Julia | October 2022

October 13, 2022 | El Salvador
This report
highlights changes in population densities as of October 13, 2022 along the west coast of El Salvador, where destruction from Tropical Storm Julia is most severe.

Key Observations:

  • Population densities in the several areas along the west coast of El Salvador continued to rise at the time of analysis (October 13, 2022). Population levels have increased since the last period of analysis on October 12, indicating that there is a steady stream of return of people temporarily displaced by the storm.
  • Despite rising densities in the areas located inland from the western coastline and in the southern region of the country, populations along the coast line are still below baseline levels. Even though these areas are below baseline values, they have shown increased densities since our previous reports on October 10, when displacement was at its peak.

October 13, 2022 | Nicaragua, Western Coastline
This report
highlights changes in population densities as of October 13, 2022 along the west coast of Nicaragua, where destruction caused by Tropical Storm Julia was most severe.

Key Observations:

  • Populations in the area of analysis continue to rise to (or near) baseline population levels taken prior to Tropical Storm Julia’s landfall in Nicaragua.
  • Similarly to previous reports, the city of Rivas still shows a population density well below baseline values. However, the percentage decrease from baseline is less than our previous report on October 12, 2022.
  • Population levels increased in level 1 administrative units where displacement was most severe after Julia’s landfall.

October 12, 2022 | El Salvador, Western Coastline
This report
highlights changes in population densities along the west coast of El Salvador, where Tropical Storm Julia first made landfall in the country.

Key Observations:

  • Populations began to rise in the areas most affected by the tropical storm, indicating that people are returning to their original locations after being temporarily displaced.
  • Population densities along the western coastline are still below baseline values prior to landfall. However, these areas showed increasing densities compared to the previous report published on October 10, 2022, when displacement was at its peak.
  • Population densities identified from Facebook data remains high in the top level 1 administrative unites with the biggest population drop, indicating the patterns detected are highly reliable.

October 12, 2022 | Nicaragua, Western Coastline
This report
highlights changes in population densities along the west coast of Nicaragua, where destruction caused by Tropical Storm Julia was most severe.

Key Observations:

  • Population densities in most level 1 administrative units of Nicaragua continued to rise to — or near — the baseline population values prior to landfall at the time of analysis.
  • Rivas, Nicaragua still showed a population density significantly below its pre-landfall levels.
  • Populations in the other areas along the country’s western coastline have returned to — or near — baseline population values.

October 11, 2022 | El Salvador Coastline
As of the night of October 11, 2022, most areas of El Salvador that were directly impacted by Hurricane Julia have returned to baseline population levels. This report highlights trends in population movement patterns as rescue organizations scramble to respond to the destruction caused by Hurricane Julia.

Key Observations:

  • Significant numbers of reduced populations could be detected in areas around the capital city San Salvador, (-3%), Antiguo Custalacan (-4%), as well as the smaller surrounding towns in the La Libertad district.

October 11, 2022 | Nicaragua, Caribbean Coast
This report highlights population density change from baseline along the west coast of Nicaragua during the peak of displacement.

Key Observations:

  • Population densities in the majority of level 1 admin units in Nicaragua have risen to nearly baseline population levels, which were recorded prior to the storm’s landfall.
  • Rivas, a city in southwestern Nicaragua, showed population values significantly below the pre-landfall levels at the time of analysis.
  • As of October 11, populations in other coastal regions have returned to — or near — pre-event baseline levels.

October 10, 2022 | Northern & South-Central El Salvador
This report highlights changes in population densities in northern and south-central regions of El Salvador during the peak of displacement. Specific areas of focus include Usulutan, La Paz, La Libertad, and Sonsonate.

Key Observations:

  • Decreases in population densities were significant across the north-central and south-central regions of El Salvador, especially in areas along the west coast.
  • Usulutan, La Paz, La Libertad, and Sonsonate saw the most significant declines in population densities at the time of analysis.
  • Population densities in this region have since began to increase as of October, 11.

October 10, 2022 | Southwest El Salvador
Hurricane Julia made its way up the western coast of El Salvador on October 10, 2022, affecting a number of coastal regions. This report highlights changes in population densities after Julia made landfall.

Key Observations:

  • Areas showing significant population declines at the time of analysis include the near-coastal areas of Alegria, Concepcion Batres, Berlin, Jucaran, and Tecapan. All of these areas saw declines between 25% and 38% on October 9 and 10.
  • Representativeness of Facebook population in Alegria in particular is relatively high, including nearly 10% of the local population in the baseline sample.

October 9, 2022 | Nicaragua
Hurricane Julia made landfall on the Caribbean coast of Nicaragua early on Sunday, October 9 as a Category 1 Storm. The storm had sustained winds of 85 mph when it moved onshore near Laguna de Perlas around 1:15 AM (GMT-6).

This report provides an overview of population density changes from baseline numbers after the hurricane made landfall. A more granular view of population movement in Nicaragua can be found here. A report with Admin Level 3 data can be found here.

Catastrophic Flooding in Pakistan | October 2022

October 6 – October 9, 2022 | Pakistan (National Level)
This report provides an overview of population density changes at a national level.

Key Observations:

  • The western regions of Pakistan experienced the largest declines in population density from August 24 to 30, 2022, reflecting the period of peak flash flooding in Balochistan.
  • The average population density has gradually increased across regions throughout the country after August 30th, regardless of the number of Facebook users in each region relative to total population
  • Among all admin level 2 units, Sibi and Nasirabad saw the lowest proportion of population return in the wake of peak flooding.
  • The greatest increases in population density for urban areas directly proximate to heavy flooding occurred in Multan and Peshawar between August 29 and Sept 9.

October 6 – October 9, 2022 | Balochistan Province
This report
provides an overview of population density and mobility changes in Balochistan, Pakistan.

Key Observations:

  • The majority of administrative units in Balochistan saw significant population decreases compared to pre-event baseline during the peak of displacement.
  • Kalat, Nasirabad, and Quetta recorded significant population drops from August 23 to September 4.
  • Population remained much lower than pre-event baseline levels in Sibi for more than30 days. This trend started on August 13 and did not change until September 20.
  • During the peak of population displacement (August 23 – September 4), mobility across level 2 units dropped everywhere except Makran.

October 6 – October 9, 2022 | Sindh Province
This report provides an overview of population density changes in the Sindh province of Pakistan.

Key Observations:

  • Sindh recorded two peaks of population displacement, one before August 20, the other from August 23 to 29. In Sindh, population remained much lower than pre-event baseline for a shorter period of time compared to Balochistan.
  • Sukkur’s population remained lower than baseline for a longer time than other level 2 admin units in Sindh.
  • During both peaks of population displacement, rates of mobility also dropped significantly in Sindh. Although some increases in rates of mobility movement could be detected in level 2 admin units in Sindh on August 21 & 22, those increases may also be attributed to the urban commuting pattern that occurs periodically in these areas.
  • Hyderabad, Larkana, Mirpur Khas, and Sukkur are the level 2 admin units with the most prominent decreases in mobility.

October 6 – October 9, 2022 | Khyber-Pakhtunkhwa Province
This report provides an overview of population density changes in the Khyber-Pakhtunkhwa province of Pakistan

Key Observations:

  • Khyber-Pakhtunkhwa (K-P) recorded two peaks of population displacement, one beforeAugust 20, the other from August 23 to 29.
  • The population of Dera Ismail Khan remained lower than baseline for longer than other level 2 admin units in K-P.
  • Hazara and Makaland witnessed the longest period with significant decrease in mobility.
  • The decrease in mobility for K-P coincided with the two major peaks of population displacement and lasted until September 21.

Hurricane Ian | September – October 2022

October 9, 2022 | Southwest Florida, United States

This report provides an overview of population movement and density changes as of October 9, 2022 throughout southwest Florida.

Key Observations:

  • A number of towns that were heavily impacted by Hurricane Ian are still showing significant reductions in population densities. In particular, Fort Meyers Beach and Sanibel Island show either reductions approaching 100% or complete lack of signal.
  • Areas including St. James City, Pineland, Bokeelia, Pine Island Center, and Mattacha, which have seen similar extreme losses in population in earlier days post-landfall began to see signs of recovery in population as of October 8.
  • More than half of the towns and cities featured in this report indicate full recovery to pre-landfall baseline populations.

October 4, 2022 | Southwest Florida, United States
This report provides an overview of population movement and vulnerability data (collected on October 4) from areas throughout southwest Florida.

Key Observations:

  • As of October 4, widespread power outages persisted across the entirety of southwest Florida, proximate to the landfall of Hurricane Ian.
  • Rates of return throughout the affected areas are above baseline except for the most affected counties (i.e. Charlotte and Lee).
  • Even in Charlotte and Lee counties, population densities have nearly returned to baseline numbers.
  • The rate of return remains linear day-over-day, which forecasts full return across the region by October 10th or 11th.

October 2, 2022 | Florida, United States
As of October 2, 2022, counties across Florida that have been most impacted by Hurricane Ian continue to see widespread power outages and reductions in population densities.

This report provides updated data on population movement and vulnerabilities.

Key Observations:

  • Charlotte and Lee Counties, located on the southwestern coast of Florida, saw population reductions between 14% and 26% at the time of analysis.
  • Most counties surrounding Charlotte and Lee, extending to the eastern side of the state, have seen relatively significant increases in population densities.
  • The most proximate increase to the western area of landfall occurred in Hillsborough County, which saw an increase in Facebook users of nearly 26,000 (9%) relative to baseline values of 90-days pre-crisis.

October 1, 2022 | Southwest Florida, United States (American Community Survey Data)
This report provides a granular view of population movement and community vulnerability dynamics for the areas along the southwest coast of Florida, which have been most impacted by Ian.

Key Observations:

  • As of October 1, the areas showing the greatest decrease in population include Fort Meyers Beach (-94%), St. James City (-93%), and Pine Island Center (-93%). These areas show no current signs of return, given the level of infrastructure damage.
  • Evacuations throughout the region were substanial and widespread, with many cities and towns still reduced by 10% or more (as of October 1).
  • However, many areas have seen significant rates of return above baseline at the time of analysis. Most notable among these areas is the mid-sized town of Lehigh Acres, which was above the baseline population by 9% (with an increase of nearly 2,000 people at the time of analysis).

October 1, 2022 | Southwest Florida, United States
This report
summarizes population movement patterns and vulnerability indicators for the coastal southwest of Florida in the aftermath of Hurricane Ian’s landfall in the state.

Key Observations:

  • Steady rates of return were detected in most Florida counties at the time of analysis on October 1.
  • Sarasota, Hardee, DeSoto, Lee, and Charlotte counties remain at 10% below baseline population values, with Charlotte seeing the most severe ongoing decline at -40%.
  • However, the rates of population decrease are in comparison to peak declines of roughly 65% in the most affected areas.
  • The more northern and inland counties of Manatee, Hendry, Glades, Collier, and Highland are all seeing population increases relative to baseline values at the time of analysis. The increases range from 2% to 14%.

October 1, 2022 | East Coast of South Carolina, United States
This report summarizes population movement patterns and vulnerability indicators for the East Coast of South Carolina after Hurricane Ian made landfall in the state.

Key Observations:

  • The greatest decreases in population occured in the counties of Horry and Brunsqick, located north of Charleston. These counties saw consistent day-over-day declines of 13% to 14%, as compared to 5% to ^% in the more southern counties of Charleston and Brunswick.
  • The counties inland from these coastal areas generally saw either no change or a slight increase in population, which reflects the relatively short average distances traveled by evacuees from Horry and Brunswick.
  • The population of Horry, Brunswick, and Georgetown are generally more vulnerable to disaster impacts. The number of residents over the age of 65 ranges as high at 31%, and poverty rates range as high as 16%.

September 30, 2022 | Charleston Region, South Carolina, United States
This report
highlights age vulnerabilities in the regions affected by Hurricane Ian after it made landfall in South Carolina. The report also sheds light on population movement patterns in and around Charleston.

Key Observations:

  • Age vulnerabilities are relatively significant in this region. The counties in the immediate path of the hurricane range from a low of 14% of the population over the age of 65 to a high of 28%.
  • In some areas, particularly on a number of islands off the Atlantic coast, the proportion of residents over the age of 65 grows to 40% or more of the total population.
  • Orangeburg, Williamsburg, and Clarendon Counties are the areas in the hurricane’s path with the highest proportion of people living in poverty, with rates between 21% and 23%.
  • South Carolina has not yet experiences power outages to any significant degree. However, the recent experience in Florida shows that widespread outages are likely. Rates of users of power-dependent medical equipment are relatively low to in-line with the national average, with the exception of Horry County, which has a rate of DME users roughly 4x the average U.S. county.

September 28, 2022 | Charlotte County, Western Florida, United States (Post-Landfall)
This is a specific report for Charlotte County, Florida, after Hurricane Ian made landfall on Thursday, September 28 at 1800 EDT. The report shows changes in population density as well as data on community vulnerabilities and power outages.

Key Observations:

  • There was a large decrease in population density by 74% in Charlotte County, suggested from our daily analyses that people continued to evacuate shortly before the hurricane made landfall.
  • According to the American Community Survey (ACS), ~29% of Charlotte County’s population are 65 years of age or older, with a higher percentage of those over 65 in the path of the hurricane and in the coastal areas.
  • At the time of analysis, there was a significant increase in power outages in the county. Our power data sources are unable to show outages at the place or sub-county level at this time.

September 28, 2022 | Lee County, Western Florida, United States (Post-Landfall)
This is a specific report for Lee County, Florida, after Hurricane Ian made landfall on Thursday, September 28 at 1800 EDT. The report shows changes in population density as well as data on community vulnerabilities and power outages.

Key Observations:

  • There was a large decrease in population density by 65% in Lee County, suggested from our daily analyses that people continued to evacuate shortly before the hurricane made landfall.
  • According to the American Community Survey (ACS), ~29% of Lee County’s population are 65 years of age or older, with a higher percentage of those over 65 in the path of the hurricane and in the coastal areas.
  • At the time of analysis, there was a significant increase in power outages in the county. Our power data sources are unable to show outages at the place or sub-county level at this time.

September 28, 2022 | Central & Eastern Florida, United States
Hurricane Ian passed over the Central and Eastern regions of Florida on Thursday, September 29 at Category 1 strength. This report provides information on Ian’s forecasted path, and the densities and vulnerabilities within it.

Key Observations:

  • Power outages were not prevalent throughout central and eastern Florida at the time of analysis. Only modest outages reported in Volusia, Brevard, and Orange Counties.
  • Most areas in the region showed population increases, due in part to evacuations ordered in Southwestern Florida, which bore the brunt of the storm.
  • Coastal areas, including Daytona Beach and Cocoa Beach, showed modest declines between 1% and 9%. Areas from Kissimmee to Alafaya showed increases in population between 7% and 10%.
  • Volusia and Brevard Counties have a high percentage of elderly residents at 24%, with over 13,000 users of power-dependent medical devices between the two counties.
  • Orange county has a younger population compared to the other nearby, with only 12% of residents over the age of 65. Given its relatively higher total population, it has roughly the same average number of power-dependent medical device users as Volusia and Brevard.

September 28, 2022 | Charlotte & Lee Counties, Florida, United States (Combined Report)
This report provides data on Hurricane Ian’s predicted path after making landfall on the west coast of Florida. Additionally, the report outlines population mobility and power outage data around Charlotte and Lee Counties, which were most affected by the storm’s initial landfall.

Key Observations:

  • Charlotte and Lee Counties saw population reductions between 65% and 74%. These reducations took place a day before the hurricane made landfall.
  • The report shows that more than 100,000 people still remained in heavily-flooded coastal areas (i.e. Charlotte, Lee, Sarasota, DeSoto Counties) at the time of analysis.
  • No town or municipality in the geographic area of focus reported increasing population densities.
  • On the lower end, areas such as Sebring and Lakewood Ranch showed declining population densities between 1% and 22%.
  • On the higher end, areas such as Cape Coral and Port Charlotte showed declining population densities of 74% or more.
  • Severe power outages took place in Manatee, Collier, Lee, and Sarasota Counties, affecting 100% of customers. Cumulatively, those counties contain nearly 17,000 people registered as using power dependent medical devices.

September 27, 2022 | West Coast Florida, United States
This report summarizes vulnerability and mobility data of the regions south of Tampa Bay, Florida, namely Charlotte, Sarasota, Lee, and DeSoto Counties. This region was predicted to be the initial site of landfall in the United States.

Key Observations:

  • Although relatively significant decreasing movement trends can be detected, especially in smaller coastal communities, some areas are showing increasing population trends over September 26 and 27.
  • Charlotte County, in particular, was still showing a large number of people who have not evacuated at the time of analysis.
  • Each of the four counties (Charlotte, Sarasota, Lee, DeSoto) experienced power outage prior to storm’s landfall.
  • Lee and Sarasota counties experienced the highest rates of power outage at the time of analysis. These counties also contain numbers of residents with power dependent medical devices above the state average.

Catastrophic Floods in Pakistan | August – September 2022

September 13, 2022 | Pakistan (National-Level)
The updated maps below shed light on the evolving displacement patterns as floods continue to devastate Pakistan. A new data layer has been added in the maps below to show the population change at administrative level 2, as the tile level population update has recently encountered issues.

Key Observations:

  • Most areas, especially the populous cities in the Northeast part of Pakistan, have returned to pre-crisis population levels at the time of analysis.
  • The flooded zones of the south still experienced significant decreases in population densities as of September 13, 2022.
  • Population mobility trends show heavy movement out of areas surrounding Hyderabad and Karachi, and into more northern cities like Lahore, Multan, and Quetta.

Population Movement Map


September 5, 2022 | Pakistan (National-Level)
The interactive map
below shows population movement patterns driven by recent floods in Pakistan between August 13, 2022 and September 5, 2022.

Interpretation:

  • The red arrows on the map show the directional patterns of population movement. The size (width) of the arrows correlates with the the volume of individuals displaced from the selected origins.
  • The larger the arrow, the greater number of movement vectors.
  • Transparency of arrows indicates the baseline population traveling between the origin and the destination under the pre-crisis situation.
  • The maps were generated using data provided by Data for Good at Meta. For more information about the disaster population maps provided by Data for Good at Meta, please refer to this link.

August 30, 2022 | Pakistan (National-Level)
This map shows population changes compared to pre-crisis baseline in Pakistan on a daily basis for all level 3 administrative units for Pakistan.

Data Sources & Interpretation:

  • The data is time-enabled to show the change from August 13, 2022 to the latest date when population change data harvested by Data for Good at Meta is available.
  • Population maps provided by Data for Good at Meta are generated based on users of Facebook.
  • Data on flood extent is gathered using the Visible Infrared Imaging Radiometer Suite (VIIRS), an instrument that collects visible and infrared images and global observations of the land, atmosphere, cryosphere, and oceans.

Mill Fire, Siskiyou County, California, United States | September 2022

September 5, 2022 | Siskiyou, Trinity, Shasta Counties, California, United States
This report highlights the most recent changes in population densities in the areas most affected by the Mill Fire in northern California, namely Siskiyou, Trinity, and Shasta Counties.

*Note: As of September 5, the fire perimeter and power outage data for the Mill Fire report is not displaying properly.

Key Observations:

  • The most populous counties affected by the fire are Siskiyou County, Trinity County, and Shasta County, with pre-crisis populations of 6,145, 1,360, and 31,816 respectively
  • At the time of analysis, the population density of Siskiyou County increased by 13% from baseline values.
  • Trinity County’s population increased by 5%.
  • Shasta County’s population decreased by 3%.

March 26, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

26 March, 2022

Summary: The following data maps show population density changes between March 20, 2022 and March 26, 2022 in Poland, Hungary, Romania, and Slovakia.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint data from the Humanitarian Data Exchange (HDX), refugee reception point data from the Government of Poland, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


March 22, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

22 March, 2022

Summary: The following data maps show population density changes between March 16, 2022 and March 22, 2022 in Poland, Hungary, Romania, and Slovakia.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint data from the Humanitarian Data Exchange (HDX), refugee reception point data from the Government of Poland, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


March 20, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

20 March, 2022

Summary: The following data maps show population density changes between March 14, 2022 and March 20, 2022 in Poland, Hungary, Romania, and Slovakia.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint data from the Humanitarian Data Exchange (HDX), refugee reception point data from the Government of Poland, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


March 19, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

19 March, 2022

Summary: The following data maps show population density changes between March 14, 2022 and March 19, 2022 in Poland, Hungary, Romania, and Slovakia.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint data from the Humanitarian Data Exchange (HDX), refugee reception point data from the Government of Poland, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia

Interpretation

  • Decreases in population density changes are reflected by brown dots.
  • Increases in population density changes are reflected by green dots.
  • Similarly to previous maps, the saturation and transparency of the colored dots reflect the strength of changes in population densities. The transparency of the dots also reflects the confidence in data representativeness.
  • Higher saturation = greater rate of change.
  • Lower saturation = lower rate of change. 
  • Low transparency/high saturation higher confidence in data representativeness. 
  • High transparency/low saturation = lower confidence in data representativeness

March 16, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

16 March, 2022

Summary: The following data maps show population density changes between March 10, 2022 and March 16, 2022 in Poland, Hungary, Romania, and Slovakia.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint data from the Humanitarian Data Exchange (HDX), refugee reception point data from the Government of Poland, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


March 15, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

15 March, 2022

Summary: The following data maps show population density changes between March 9, 2022 and March 15, 2022 in Poland, Hungary, Romania, and Slovakia.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint data from the Humanitarian Data Exchange (HDX), refugee reception point data from the Government of Poland, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


March 14, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

14 March, 2022

Summary: The following data maps show population density changes between March 8, 2022 and March 14, 2022 in Poland, Hungary, Romania, and Slovakia.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint data from the Humanitarian Data Exchange (HDX), refugee reception point data from the Government of Poland, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


March 13, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

13 March, 2022

Summary: The following data maps show population density changes between March 7, 2022 and March 13, 2022 in Poland, Hungary, and Romania.
Note: Slovakia did not have data available for March 13, 2022.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint data from the Humanitarian Data Exchange (HDX), refugee reception point data from the Government of Poland, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania


March 8, 2022 | Social Connectedness & Population Density Change Map Analyses of Countries Bordering Western Ukraine

8 March, 2022

Summary: The following data maps show population density changes between March 3, 2022 and March 8, 2022 in Poland, Hungary, Slovakia, and Romania compared with their social connectedness with Ukraine.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) Meta’s Social connectedness index (SCI,) a measurement based on Facebook friendship connections of Ukraine users, and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia

All Countries: SCI & Population Density Change


Interactive Map: Population Density Change Map Analysis of Countries Bordering Western Ukraine

7 March, 2022

Summary: The interactive map below shows changes in population densities and refugee reception points along the Poland-Ukraine border as of March 7, 2022.

Data Sources: This map was generated using human mobility data gathered from Meta’s Data for Good initiative and border checkpoint information from HDX.

Note: To interact with the map below, click and drag the time selection tool. Information relating to the selected timeframe will be displayed above the time selection tool. Users may also move the map by clicking and dragging your cursor until the desired region is shown. Users may disable 3D mapping visualization, access the legend, draw a specific region on the map, or change the language by clicking the widgets displayed in the upper right hand corner.

Interactive Map: Changes in Population Densities Along the Poland-Ukraine Border


March 6, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

6 March, 2022

Summary: The following data maps show population density changes between March 1, 2022 and March 6, 2022 in Poland, Hungary, Slovakia, and Romania.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


March 5, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

5 March, 2022

Summary: The following data maps show population density changes between February 24, 2022 and March 5, 2022 in Poland, Hungary, Slovakia, and Romania.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


March 2, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

2 March, 2022

Summary: The following data maps show population density changes between February 24, 2022 and March 2, 2022 in Poland, Hungary, Slovakia, and Romania.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) and regional data gathered from the European Commission using NUTS-3 administrative units.

Poland

Hungary

Romania

Slovakia


February 26, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

26 February, 2022

Summary: The following data map shows population density changes as of February 26, 2022 along the Poland-Ukraine border.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint information from HDX, and regional data gathered from the European Commission using NUTS-3 administrative units.

Population Density Changes: Poland-Ukraine Border


February 26, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

26 February, 2022

Summary: The following data map shows population density changes and refugee reception points along the Poland-Ukraine border as of February 26, 2022.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint information from HDX.

Population Density Changes & Refugee Reception Points: Poland-Ukraine Border


February 26, 2022 | Population Density Change Map Analysis of Countries Bordering Western Ukraine

25 February, 2022

Summary: The following data map shows population density changes and refugee reception points along the Poland-Ukraine border as of February 25, 2022.

Data Sources: These data visualizations were generated using mobility data from Meta (formerly Facebook,) border checkpoint information from HDX.

Population Density Changes: Poland-Ukraine Border


Widespread Power Outages Caused by Winter Storms, United States

Report: Power-Dependent Medical Equipment Users Affected by Power Outages in Tennessee, West Virginia, Pennsylvania, Ohio, Texas, and New York

Date: 4 February, 2022
Note: This data visualization originally appeared on Direct Relief news service.

Storm Landon, Northern Texas, United States

Report: Power-Dependent Medical Equipment Users Affected by Power Outages in Texas

Date: 3 February, 2022
Note: This data visualization originally appeared on Direct Relief news service.

Marshall Fire, Boulder County, Colorado, United States

Report: Population density changes throughout Boulder County, Colorado.

Date: 30 December, 2021 – 5 January, 2022 (2359 hrs)

Report: Population movement matrix of regions throughout Boulder County, Colorado.

Date: 31 December, 2021
Date: 4 January, 2022

Long-track Tornado in Western Kentucky, Central United States

Report: Population Density Changes

Date: 14 December, 2021 (2359 hrs)
Date: 11 – 12 December, 2021 (2100 – 2320 hrs)

Caldor Fire in El Dorado County, California

Report: Population Density Changes

Date: 6 – 7 September, 2021 (1600 – 2359 hrs)

ArcGIS Layer – Population Density Changes

Period: 23 – 29 August, 2021

Archived Reports

Period: 29 August – 5 September, 2021
Caldor Wildfire Sitrep 6 September 2021
Caldor Wildfire Sitrep 2 September 2021
Caldor Wildfire Sitrep 1 September 2021
Caldor Wildfire Sitrep 29 August 2021

Hurricane Ida in Orleans Parish, Louisiana


Report – Population Density Changes

Date: 7 – 8th September, 2021

Archived Reports

Period: 26 August – 7 September
Hurricane Ida Sitrep 6-7 September 2021
Hurricane Ida Sitrep 5-6 September 2021
Hurricane Ida Sitrep 1-5 September 2021
Hurricane Ida Sitrep 31 August – 1 September 2021
Hurricane Ida Sitrep 30 – 31 August 2021
Hurricane Ida Sitrep 29 – 30 August 2021
Hurricane Ida Sitrep 26 – 29 August 2021

Earthquake in Les Cayes, Haiti


Report – Network Coverage

Date: 14th – 22nd August, 2021

Dixie Wildfire in Plumas County, California


Report

Date: 14th – 22nd August, 2021

Wildfires in Attica, Greece


Report

Date: 04th – 09th August, 2021

Floods in Western Germany


Report

Date: 15th – 17th July, 2021

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