Inflation was the most worrying topic worldwide as of January 2025, with one third of the respondents choosing that option. Crime and violence as well as poverty and social inequality followed behind. Moreover, following Russia's invasion of Ukraine and the war in Gaza, nine percent of the respondents were worried about military conflict between nations. Only four percent were worried about the COVID-19 pandemic, which dominated the world after its outbreak in 2020. Global inflation and rising prices Inflation rates have spiked substantially since the beginning of the COVID-19 pandemic in 2020. From 2020 to 2021, the worldwide inflation rate increased from 3.5 percent to 4.7 percent, and from 2021 to 2022, the rate increased sharply from 4.7 percent to 8.7 percent. While rates are predicted to fall come 2025, many are continuing to struggle with price increases on basic necessities. Poverty and global development Poverty and social inequality was the third most worrying issue to respondents. While poverty and inequality are still prominent, global poverty rates have been on a steady decline over the years. In 1994, 64 percent of people in low-income countries and around one percent of people in high-income countries lived on less than 2.15 U.S. dollars per day. By 2018, this had fallen to almost 44 percent of people in low-income countries and 0.6 percent in high-income countries. Moreover, fewer people globally are dying of preventable diseases and people are living longer lives. Despite these aspects, issues such as wealth inequality have global prominence.

A survey of people from 31 different countries around the world found that mental health was the biggest health problem respondents said was facing their country in 2024. Other health problems reported by respondents included cancer, stress, and obesity. The COVID-19 pandemic The COVID-19 pandemic impacted almost every country in the world and was the biggest global health crisis in recent history. It resulted in hundreds of millions of cases and millions of deaths, causing unprecedented disruption in health care systems. Lockdowns imposed in many countries to halt the spread of the virus also resulted in a rise of mental health issues as feelings of stress, isolation, and hopelessness arose. However, vaccines to combat the virus were developed at record speed, and many countries have now vaccinated large shares of their population. Nevertheless, in 2024, 11 percent of respondents still stated that COVID-19 was the biggest health problem facing their country. Mental health issues One side effect of the COVID-19 pandemic has been a focus on mental health around the world. The two most common mental health issues worldwide are anxiety disorders and depression. In 2021, it was estimated that around 4.4 percent of the global population had an anxiety disorder, while four percent suffered from depression. Rates of depression are higher among females than males, with some 4.3 percent of females suffering from depression, compared to 2.9 percent of men. However, rates of suicide in most countries are higher among men than women. One positive outcome of the COVID-19 pandemic and the spotlight it shined on mental health may be a decrease in stigma surrounding mental health issues and seeking help for such issues. This would be a positive development as many people around the world do not or cannot receive the necessary treatment they need for their mental health.

This study is part of a quadrennial series designed to investigate the opinions and attitudes of the general public on matters related to foreign policy, and to define the parameters of public opinion within which decision-makers must operate. This public opinion study of the United States focused on respondents' opinions of the United States' leadership role in the world and the challenges the country faces domestically and internationally. The survey covered the following international topics: relations with other countries, role in foreign affairs, possible threats to vital interests in the next ten years, foreign policy goals, benefits or drawbacks of globalization, situations that might justify the use of United States troops in other parts of the world, the number and location of United States military bases overseas, respondent feelings toward people of other countries, opinions on the influence of other countries in the world and how much influence those countries should have, whether there should be a global regulating body to prevent economic instability, international trade, United States participation in potential treaties, the United States' role in the United Nations and NATO, respondent opinions on international institutions and regulating bodies such as the United Nations, World Trade Organization, and the World Health Organization, whether the United States will continue to be the world's leading power in the next 50 years, democracy in the Middle East and South Korea, the role of the United Nations Security Council, which side the United States should take in the Israeli-Palestinian conflict, what measures should be taken to deal with Iran's nuclear program, the military effort in Afghanistan, opinions on efforts to combat terrorism and the use of torture to extract information from prisoners, whether the respondent favors or opposes the government selling military equipment to other nations and using nuclear weapons in various circumstances, the economic development of China, and the conflict between North and South Korea. Domestic issues included economic prospects for American children when they become adults, funding for government programs, the fairness of the current distribution of income in the United States, the role of government, whether the government can be trusted to do what is right, climate change, greenhouse gas emissions, United States' dependence on foreign energy sources, drilling for oil and natural gas off the coast of the United States, and relations with Mexico including such issues as the ongoing drug war, as well as immigration and immigration reform. Demographic and other background information included age, gender, race/ethnicity, marital status, left-right political self-placement, political affiliation, employment status, highest level of education, and religious preference. Also included are household size and composition, whether the respondent is head of household, household income, housing type, ownership status of living quarters, household Internet access, Metropolitan Statistical Area (MSA) status, and region and state of residence.

This statistic displays the issues that are caused by climate change globally according to residents in the United Kingdom (UK) in 2018. Weather issues were the most common effects of climate change according the the respondents. 84 percent of respondents feel that increased extreme weather in the UK is caused by climate change now or in the future.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.6/22/2020 - Added Executive Summary and Subsequent Outbreaks sectionsRevisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Correction on 6/1/2020Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Revisions added on 4/30/2020 are highlighted.Revisions added on 4/23/2020 are highlighted.Executive SummaryCOVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties. The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.Reasons for undertaking this work in March of 2020:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Data here cover child labor, gender issues, refugees, and asylum seekers. Children in many countries work long hours, often combining studying with work for pay. The data on their paid work are from household surveys conducted by the International Labour Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. Gender disparities are measured using a compilation of data on key topics such as education, health, labor force participation, and political participation. Data on refugees are from the United Nations High Commissioner for Refugees complemented by statistics on Palestinian refugees under the mandate of the United Nations Relief and Works Agency.

Updates

• Notice of data discontinuation: Since the start of the pandemic, AP has reported case and death counts from data provided by Johns Hopkins University. Johns Hopkins University has announced that they will stop their daily data collection efforts after March 10. As Johns Hopkins stops providing data, the AP will also stop collecting daily numbers for COVID cases and deaths. The HHS and CDC now collect and visualize key metrics for the pandemic. AP advises using those resources when reporting on the pandemic going forward.

  • CDC Weekly case and death counts (national and state level)
  • CDC County level cases and deaths
  • HHS New hospital admissions
  • CDC NowCast COVID variant proportions (national and regional level)

• April 9, 2020

  • The population estimate data for New York County, NY has been updated to include all five New York City counties (Kings County, Queens County, Bronx County, Richmond County and New York County). This has been done to match the Johns Hopkins COVID-19 data, which aggregates counts for the five New York City counties to New York County.

• April 20, 2020

  • Johns Hopkins death totals in the US now include confirmed and probable deaths in accordance with CDC guidelines as of April 14. One significant result of this change was an increase of more than 3,700 deaths in the New York City count. This change will likely result in increases for death counts elsewhere as well. The AP does not alter the Johns Hopkins source data, so probable deaths are included in this dataset as well.

• April 29, 2020

  • The AP is now providing timeseries data for counts of COVID-19 cases and deaths. The raw counts are provided here unaltered, along with a population column with Census ACS-5 estimates and calculated daily case and death rates per 100,000 people. Please read the updated caveats section for more information.

• September 1st, 2020

  • Johns Hopkins is now providing counts for the five New York City counties individually.

• February 12, 2021

  • The Ohio Department of Health recently announced that as many as 4,000 COVID-19 deaths may have been underreported through the state’s reporting system, and that the "daily reported death counts will be high for a two to three-day period."
  • Because deaths data will be anomalous for consecutive days, we have chosen to freeze Ohio's rolling average for daily deaths at the last valid measure until Johns Hopkins is able to back-distribute the data. The raw daily death counts, as reported by Johns Hopkins and including the backlogged death data, will still be present in the new_deaths column.

• February 16, 2021

  - Johns Hopkins has reconciled Ohio's historical deaths data with the state.

  Overview

The AP is using data collected by the Johns Hopkins University Center for Systems Science and Engineering as our source for outbreak caseloads and death counts for the United States and globally.

The Hopkins data is available at the county level in the United States. The AP has paired this data with population figures and county rural/urban designations, and has calculated caseload and death rates per 100,000 people. Be aware that caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.

This data is from the Hopkins dashboard that is updated regularly throughout the day. Like all organizations dealing with data, Hopkins is constantly refining and cleaning up their feed, so there may be brief moments where data does not appear correctly. At this link, you’ll find the Hopkins daily data reports, and a clean version of their feed.

The AP is updating this dataset hourly at 45 minutes past the hour.

To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

Queries

Use AP's queries to filter the data or to join to other datasets we've made available to help cover the coronavirus pandemic

• Filter cases by state here

• Rank states by their status as current hotspots. Calculates the 7-day rolling average of new cases per capita in each state: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=481e82a4-1b2f-41c2-9ea1-d91aa4b3b1ac

• Find recent hotspots within your state by running a query to calculate the 7-day rolling average of new cases by capita in each county: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=b566f1db-3231-40fe-8099-311909b7b687&showTemplatePreview=true

• Join county-level case data to an earlier dataset released by AP on local hospital capacity here. To find out more about the hospital capacity dataset, see the full details.

• Pull the 100 counties with the highest per-capita confirmed cases here

• Rank all the counties by the highest per-capita rate of new cases in the past 7 days here. Be aware that because this ranks per-capita caseloads, very small counties may rise to the very top, so take into account raw caseload figures as well.

Interactive

The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.

@(https://datawrapper.dwcdn.net/nRyaf/15/)

Interactive Embed Code

<iframe title="USA counties (2018) choropleth map Mapping COVID-19 cases by county" aria-describedby="" id="datawrapper-chart-nRyaf" src="https://datawrapper.dwcdn.net/nRyaf/10/" scrolling="no" frameborder="0" style="width: 0; min-width: 100% !important;" height="400"></iframe><script type="text/javascript">(function() {'use strict';window.addEventListener('message', function(event) {if (typeof event.data['datawrapper-height'] !== 'undefined') {for (var chartId in event.data['datawrapper-height']) {var iframe = document.getElementById('datawrapper-chart-' + chartId) || document.querySelector("iframe[src*='" + chartId + "']");if (!iframe) {continue;}iframe.style.height = event.data['datawrapper-height'][chartId] + 'px';}}});})();</script>

Caveats

• This data represents the number of cases and deaths reported by each state and has been collected by Johns Hopkins from a number of sources cited on their website.
• In some cases, deaths or cases of people who've crossed state lines -- either to receive treatment or because they became sick and couldn't return home while traveling -- are reported in a state they aren't currently in, because of state reporting rules.
• In some states, there are a number of cases not assigned to a specific county -- for those cases, the county name is "unassigned to a single county"
• This data should be credited to Johns Hopkins University's COVID-19 tracking project. The AP is simply making it available here for ease of use for reporters and members.
• Caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.
• Population estimates at the county level are drawn from 2014-18 5-year estimates from the American Community Survey.
• The Urban/Rural classification scheme is from the Center for Disease Control and Preventions's National Center for Health Statistics. It puts each county into one of six categories -- from Large Central Metro to Non-Core -- according to population and other characteristics. More details about the classifications can be found here.

Johns Hopkins timeseries data - Johns Hopkins pulls data regularly to update their dashboard. Once a day, around 8pm EDT, Johns Hopkins adds the counts for all areas they cover to the timeseries file. These counts are snapshots of the latest cumulative counts provided by the source on that day. This can lead to inconsistencies if a source updates their historical data for accuracy, either increasing or decreasing the latest cumulative count. - Johns Hopkins periodically edits their historical timeseries data for accuracy. They provide a file documenting all errors in their timeseries files that they have identified and fixed here

Attribution

This data should be credited to Johns Hopkins University COVID-19 tracking project

This Voice of the People poll seeks the opinions of Canadians, on predominantly economic, political, and social issues. The questions ask opinions of the state of the economy, business and political leaders and predictions for 2006, and world progress. There are also questions on other topics of interest such as job safety, news media, world issues, and industrial disputes. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: global economy; 2006; job safety; media; and industrial disputes. Basic demographic variables are also included.

This dataset provides values for CORONAVIRUS CASES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The starting point for the research has been the list of 147 banking crises within the period 1976-2011 prepared by the International Monetary Fund. The countries with crises have been analysed with respect to publicly available World Bank indicators in the periods of three years before the crises. The machine learning methodology for subgroup discovery has been used for the analysis. It enabled identification of five subsets of crises. Two of them have been identified as especially useful for the characterization of EU countries with banking crises in the year 2008. Fast growing credit activity is characteristic for the first subgroup while socioeconomic problems recognized by non-increasing quality of public health are decisive for the second subgroup. Comparative analysis of EU countries included into these subgroups demonstrated statistically significant differences with respect to World Bank good governance indicator values for the period before the crisis. Control of corruption, rule of law, and government effectiveness are the indicators which are statistically different for these sets of countries. The significance of the result is in the segmentation of the corpus of countries with banking crises and the recognition of connections between banking crises, socioeconomic problems, and governance effectiveness in some EU countries

According to an April 2024 survey on climate change conducted in the United States, some 66 percent of the respondents claimed they rarely or never discuss global warming with family and friends. Another 35 percent reported that they often or occasionally discussed the topic.

Ireland Current Economic Conditions Index data was reported at 110.302 4Q1995=100 in Oct 2018. This records a decrease from the previous number of 115.378 4Q1995=100 for Sep 2018. Ireland Current Economic Conditions Index data is updated monthly, averaging 103.310 4Q1995=100 from Feb 1996 (Median) to Oct 2018, with 273 observations. The data reached an all-time high of 129.607 4Q1995=100 in Jan 2018 and a record low of 63.831 4Q1995=100 in Jul 2008. Ireland Current Economic Conditions Index data remains active status in CEIC and is reported by The Economic and Social Research Institute. The data is categorized under Global Database’s Ireland – Table IE.H015: Consumer Sentiment Indicator.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Data here cover child labor, gender issues, refugees, and asylum seekers. Children in many countries work long hours, often combining studying with work for pay. The data on their paid work are from household surveys conducted by the International Labour Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. Gender disparities are measured using a compilation of data on key topics such as education, health, labor force participation, and political participation. Data on refugees are from the United Nations High Commissioner for Refugees complemented by statistics on Palestinian refugees under the mandate of the United Nations Relief and Works Agency.

The findings of the Environics Global Issues Monitor, 2001 Survey are based on the results of face-to face or telephone interviews with representative samples of about 1,000 citizens in each of 20 countries on five continents. Environics 2001 Global Issues Monitor survey was conducted in the following countries: Argentina, Brazil, Canada, Chile, China, France, Germany, Great Britain, India, Indonesia, Italy, Japan, Mexico, Nigeria, Russia, South Korea, Spain, Sweden, Turkey, United States. Research was conducted by respected social research institutes in each country between November 23, 2000 and February 9, 2001. In Canada, the survey was conducted by Environics Research Group Ltd. It consisted of a nation-wide telephone survey with a sample of 1,015 individuals, 18 years and older carried out between December 11 and December 19, 2000. Some of the important topics in the EGIM 2001 are: - Quality of Life - Key Issues - Trust in Institutions - Globalization - Global Governance - Population Analysis

Abstract

JHU Coronavirus COVID-19 Global Cases, by country

Documentation

PHS is updating the Coronavirus Global Cases dataset weekly, Monday, Wednesday and Friday from Cloud Marketplace.

This data comes from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). This database was created in response to the Coronavirus public health emergency to track reported cases in real-time. The data include the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries, aggregated at the appropriate province or state. It was developed to enable researchers, public health authorities and the general public to track the outbreak as it unfolds. Additional information is available in the blog post.

Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

Section 2

Included Data Sources are:

• World Health Organization (WHO): https://www.who.int/
• DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia.
• BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/
• National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml
• China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm
• Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html
• Macau Government: https://www.ssm.gov.mo/portal/
• Taiwan CDC: https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0
• US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html
• Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html
• Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance
• European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases
• Ministry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19
• Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus
• 1Point3Arces: https://coronavirus.1point3acres.com/en
• WorldoMeters: https://www.worldometers.info/coronavirus/

%3C!-- --%3E

Section 3

**Terms of Use: **

This GitHub repo and its contents herein, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

Section 4

**U.S. county-level characteristics relevant to COVID-19 **

Chin, Kahn, Krieger, Buckee, Balsari and Kiang (forthcoming) show that counties differ significantly in biological, demographic and socioeconomic factors that are associated with COVID-19 vulnerability. A range of publicly available county-specific data identifying these key factors, guided by international experiences and consideration of epidemiological parameters of importance, have been combined by the authors and are available for use:

https://github.com/mkiang/county_preparedness/

This Voice of the People poll seeks the opinions of Canadians, on predominantly economic, political, and social issues. The questions ask opinions about corruption, democracy, government, and world issues. There are also questions on topics such as the reduction and elimination of incidences of torture, familiarity with global institutions, predictions about the next generation, public school trends, and public clinics/hospitals. There are also questions on other topics of interest such as problems facing Canada, private/public sector contribution to the improvement of social services, trust in people, and globalization/globalisation. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: economy; corruption; American foreign policy; politics; next generation; elections; public schools; public clinics/hospitals; torture; global institution; democracy; and trust. Basic demographic variables are also included.

United States RMI: Northeast: Current Market Conditions (CM) data was reported at 63.000 Point in Dec 2024. This records a decrease from the previous number of 73.000 Point for Sep 2024. United States RMI: Northeast: Current Market Conditions (CM) data is updated quarterly, averaging 79.500 Point from Mar 2020 (Median) to Dec 2024, with 20 observations. The data reached an all-time high of 87.000 Point in Mar 2022 and a record low of 58.000 Point in Sep 2023. United States RMI: Northeast: Current Market Conditions (CM) data remains active status in CEIC and is reported by National Association of Home Builders. The data is categorized under Global Database’s United States – Table US.EB076: NAHB/Westlake Royal Remodeling Market Index.

Identification. Political attitudes and behaviour. Social and political commitment and integration.

Topics: Identification: country of birth; year of immigration to the Federal Republic of Germany; reasons for immigration; German citizenship; foreign citizenship; German citizenship by birth, as (late) ethnic German repatriate without or with a German citizenship, by naturalisation; year of naturalisation; previous nationality; nationality(s) of parents; country of birth of parents; desire to acquire German nationality; religion: denomination or religious community; religious group membership within Islam; pride and identification: equal opportunities in Germany; current territory of the country of origin of father and mother; identification with the country of origin of father and of mother; identification with Germany; invitation to join a German family; considerations about working in the German civil service; like to work in Germany; language spoken in the household; respect shown in Germany; more interest in politics in Germany or in the country of origin; main reasons for dissatisfaction.

Political attitudes and behaviour:

Electoral behaviour: party preference (Sunday question); alternative vote; party that the respondent would never vote for; proximity to party in Turkey (sympathy); party membership (party); political interest; satisfaction with democracy; Political knowledge: knowledge of the President of the Federal Republic of Germany; knowledge of Chancellor Angela Merkel´s party affiliation; political participation: personal opportunities for political participation in Germany and in the country of origin.

Parties, politicians, political problems: sympathy scale for the parties SPD, CDU, CSU, Die Linke, Bündnis 90/Die Grünen, FDP, and AfD; currently the most important problem in Germany; problem-solving competence of the parties; better representation of personal interests by politicians with a migration background; naming the politician.

Political fundamentalism, populism: agreement with various statements on politics, state and society (no more ideals in society, capitalism destroys the world, USA is behind the 09/11 attacks, those up there do what they want, rejection of homosexual friends, acceptance of violence in conflicts in every democracy, call for leaders, Russia as sole culprit in international conflicts, West prevents development of the Islamic world, shame on the family by Muslim woman marrying a Christian, insult as Muslim by Mohammed caricatures, literal compliance of the rules of the Koran, adaptation of the teachings of Islam to conditions of the modern world, events in Palestine typical for the contact with all Muslims, depraved sexual morals of the western society, eligibility of a Christian party for Muslims, Islam belongs to Germany, discrimination of non-German looking people, no party in Germany represents the interests of migrants, immigrants should adapt their behaviour to the German culture, who lives in Germany should learn the German language, Jews cannot be trusted).

Social and political commitment: membership in a non-profit association or organisation in Germany; type of association or organisation; memberships in the country of origin; active participation in an association, initiative or self-help group in Germany; area of active participation; start of voluntary work (number of years); impetus for taking over the activity.

Integration: most important problem of Germans with a migration background and foreigners in Germany; most suitable party for solving this problem; evaluation of the integration efforts of the CDU: sufficient commitment of the CDU for the integration of foreigners and Germans with a migration background as well as for repatriates and late repatriates.

Demography: sex; age; attainment of the highest educational qualification in the country of origin or in Germany; highest school leaving certificate; highest vocational qualification; recognition of vocational training in Germany; employment status; occupational status; satisfaction with current or last occupational activity; current or last occupational status. last job corresponds to vocational training; desire to pursue the occupation learned; self-assessment of religiousness; frequency of churchgoing; accessibility: use of the mobile phone used for the interview exclusively alone, with others or only by chance; number of other mobile phone users aged 14 and over; landline connection in the household; number of mobile phone numbers; number of landline numbers; federal state; size of location; size of household; number of persons in the household under 18 years of age.

Additionally coded: respondent ID; weighting factor; group membership (Germans without migration background, Germans with migration background or foreigners); political community size classes.

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in Vietnam or who observe activities related to social and economic development. The World Bank Group Country Opinion Survey will give the Bank's team that works in Vietnam, greater insight into how the Bank's work is perceived. This is one tool the World Bank Group uses to assess the views of its stakeholders and to develop more effective strategies that support development in Vietnam.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in Vietnam perceive the World Bank; - Obtain systematic feedback from stakeholders in Vietnam regarding: · Their views regarding the general environment in Vietnam; · Their overall attitudes toward the World Bank in Vietnam; · Overall impressions of the World Bank’s effectiveness and results, project/program related issues, knowledge work and activities, and communication and information sharing in Vietnam; and · Perceptions of the World Bank’s future role in Vietnam. - Use data to help inform Vietnam country team’s strategy.

Geographic coverage

National coverage

Analysis unit

Stakeholder

Kind of data

Sample survey data [ssd]

Sampling procedure

From March to April 2014, 1,032 stakeholders of the World Bank Group in Vietnam were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among the National Government; the National Assembly; project management units (PMUs); local government officials or staff; bilateral or multilateral agencies; private sector organizations; NGOs; the media; and academia/research institutes/think tanks.

Mode of data collection

Other [oth]

Research instrument

The questionnaire consists of 8 Sections:

A. General Issues Facing Vietnam: Respondents were asked to indicate whether Vietnam is headed in the right direction, what they thought were the three most important development priorities, and what would best achieve "shared prosperity" in Vietnam.

B. Overall Attitudes toward the World Bank Group: Respondents were asked to rate their familiarity with the WBG, its effectiveness in Vietnam, Bank staff preparedness, to what extent it should provide capacity building support to certain groups, their agreement with various statements regarding the Bank's work, and the extent to which it is an effective development partner. Respondents were also asked to indicate the Bank's greatest values and greatest weaknesses, and with which stakeholder groups the Bank should collaborate more.

C. World Bank Group's Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve development results in Vietnam, the extent to which the Bank meets Vietnam's needs for knowledge services and financial instruments, and the Bank's level of effectiveness across twenty-four development areas.

D. The World Bank Group's Knowledge Work and Activities: Respondents were asked to indicate how frequently they consult Bank knowledge work and to rate the quality of the Bank's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality.

E. Working with the World Bank: Respondents were asked to rate the extent to which various aspects of the Bank's technical assistance/advisory work contributes to solving Vietnam's development challenges and their level of agreement with a series of statements regarding working with the Bank. Respondents were also asked to indicate if the Bank operates with too much risk.

F. The Future Role of the World Bank Group in Vietnam: Respondents were asked to indicate what the Bank should do to make itself of greater value in Vietnam.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, their awareness of the Bank's Access to Information policy, and their usage of the Bank's websites. Respondents were also asked to rate their agreement with various statements regarding the Bank's communication and information sharing in Vietnam.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they currently collaborate with the WBG in Vietnam, their exposure to the Bank in Vietnam, and their geographic location.

The questionnaire was prepared in English and Vietnamese.

Response rate

A total of 501 questionnaires were completed (49% response rate).

Every day activities such as driving, burning coal for electricity, wildfires, running factories, even cooking and cleaning, release particles into the air. Besides being an irritant, small particles of 10, 2.5, 1 micrometers (PM10, PM2.5, PM1) or less are a health hazard since they can get deep into the respiratory system and damage the delicate tissues.The exposure of populations to high levels of small particles increases the risk of respiratory and cardiovascular illnesses. The World Health Organization (WHO) guidelines provide long-term and short-term exposure limits to PM10 and PM2.5:Long-term: PM10 20 µg/m³ annual mean and PM2.5 10 µg/m³ Short-term: PM10 50 µg/m³ 24-hour mean and PM2.5 25 µg/m³ Exposure to PM10 and PM2.5 above these limits may significantly impact human health.The OpenAQ Recent Conditions in Air Quality layers show the latest mass concentrations and particulate count for PM2.5, PM10, and PM1 of the stations in the OpenAQ data set with at least one value reported in the past 30 days.Source: The source information is the OpenAQ community which reports measured concentrations (µg/m³) and particle matter count (particles/cm³) on a global scale by aggregating station data from national networks of air quality.Update Frequency: It is updated every hour using the Aggregated Live Feed (ALF) methodology.Area Covered: GlobalRevisionsJan 25, 2025: Upgrade to OpenAQ API version 3"Jan 18, 2024: Update to feed routine that allows stations w/o an identifier.Jun 23, 2023: Added new fields: Location ID, Station URL; Provider, and Instrument names. The live feed routine was updated to increase reliability and improve the overall update process.Jul 21, 2022: Added service to Live Feed Status Page for active monitoring!Feb 8, 2022: Update of live feed routine to use OpenAQ API v2:Addition of PM10 and PM1 layers.Values of particle matter count (particles/cm³) to all layers.Update of field labels.Removal of SourceName field.Feb 5, 2020: Official release of Feature Service offering.This layer is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!