Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Myanmar data available from WorldPop here.

The total population in Myanmar was estimated at 54.5 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - Myanmar Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Myanmar MM: Internet Users: Individuals: % of Population data was reported at 25.073 % in 2016. This records an increase from the previous number of 21.726 % for 2015. Myanmar MM: Internet Users: Individuals: % of Population data is updated yearly, averaging 0.219 % from Dec 1990 (Median) to 2016, with 18 observations. The data reached an all-time high of 25.073 % in 2016 and a record low of 0.000 % in 1990. Myanmar MM: Internet Users: Individuals: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Myanmar – Table MM.World Bank: Telecommunication. Internet users are individuals who have used the Internet (from any location) in the last 3 months. The Internet can be used via a computer, mobile phone, personal digital assistant, games machine, digital TV etc.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Weighted average; Please cite the International Telecommunication Union for third-party use of these data.

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers. The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters. The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules. The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Unemployment Rate in Myanmar remained unchanged at 3 percent in 2024 from 3 percent in 2023. This dataset provides - Myanmar Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Poverty and Vulnerability Assessment (PVA) dataset was developed to capture the micro-level perspective of people's experiences with poverty and vulnerability and to monitor poverty and vulnerability trends on the ground. The assessment was based on a standardized questionnaire that has been developed to assess, describe, and analyse the situation of poor and vulnerable people in the HKH region. This will lead to an enhanced understanding of multiple aspects of livelihood assets, structures, and the processes that underpin such assets. It will also help determine levels of access, terms of exchange, and returns from livelihood assets as well as livelihood strategies and their outcomes for the poor.

Techsalerator’s Business Technographic Data for Myanmar (Burma): Unlocking Insights into Myanmar's Technology Landscape

Techsalerator’s Business Technographic Data for Myanmar (Burma) offers a detailed and comprehensive dataset crucial for businesses, market analysts, and technology vendors aiming to understand and engage with companies operating within Myanmar. This dataset provides deep insights into the technological landscape, capturing and organizing data related to technology stacks, digital tools, and IT infrastructure used by businesses in the country.

Please reach out to us at info@techsalerator.com or visit Techsalerator Contact.

Top 5 Most Utilized Data Fields

• Company Name: This field lists the names of companies in Myanmar, enabling technology vendors to identify potential clients and allowing analysts to examine technology adoption trends within specific businesses.

• Technology Stack: This field outlines the technologies and software solutions a company utilizes, including accounting systems, customer management software, and cloud services. Understanding a company's technology stack is essential for evaluating its digital maturity and operational needs.

• Deployment Status: This field indicates whether the technology is currently deployed, planned for future deployment, or under evaluation. Vendors can use this information to gauge the level of technology adoption and interest among companies in Myanmar.

• Industry Sector: This field specifies the industry in which the company operates, such as manufacturing, agriculture, or finance. Knowing the industry helps vendors tailor their products to sector-specific demands and emerging trends in Myanmar.

• Geographic Location: This field identifies the company's headquarters or primary operations within Myanmar. Geographic information aids in regional analysis and understanding localized technology adoption patterns across the country.

Top 5 Technology Trends in Myanmar

• Digital Payments and Fintech Solutions: The rise of digital payments and financial technology is transforming Myanmar’s financial landscape. Businesses are increasingly adopting mobile payment solutions and fintech innovations to enhance transaction efficiency and financial inclusion.

• Agricultural Technology: Given Myanmar's significant agricultural sector, there is growing interest in agri-tech solutions such as precision farming, crop management software, and automated irrigation systems to boost productivity and sustainability.

• E-commerce Growth: E-commerce is rapidly expanding in Myanmar, with businesses leveraging online platforms and digital marketing strategies to reach a broader customer base and streamline operations.

• Healthcare IT Solutions: The healthcare sector in Myanmar is adopting IT solutions such as electronic health records, telemedicine platforms, and healthcare management software to improve service delivery and patient care.

• Renewable Energy Technologies: As Myanmar seeks to enhance its energy infrastructure, there is an increasing focus on renewable energy solutions, including solar and hydroelectric power, to support sustainable development goals.

Top 5 Companies with Notable Technographic Data in Myanmar

• KBZ Bank: A leading financial institution in Myanmar, KBZ Bank is at the forefront of digital banking, implementing online banking services, mobile apps, and advanced cybersecurity measures to enhance customer experience.

• Ooredoo Myanmar: A major telecom provider, Ooredoo Myanmar is driving the country’s connectivity with high-speed internet, mobile services, and investments in network expansion, contributing to Myanmar’s digital transformation.

• Myanmar Electric Power Enterprise (MEPE): MEPE is focused on modernizing Myanmar’s electricity infrastructure, including the integration of renewable energy sources such as solar and wind power to support national energy goals.

• Shop.com.mm: As a leading e-commerce platform in Myanmar, Shop.com.mm is leveraging digital tools and technologies to facilitate online shopping and improve customer engagement across the country.

• Mogok Technology: A key player in Myanmar’s technology sector, Mogok Technology is specializing in IT solutions and services, including software development, cloud computing, and IT consulting to support various business needs.

Accessing Techsalerator’s Business Technographic Data

For those interested in accessing Techsalerator’s Business Technographic Data for Myanmar, please contact info@techsalerator.com with your specific needs. Techsalerator offers customized quotes based on the required number of data fields and records, with datasets available for delivery within 24 hours. Ongoing access options can also be arranged upon request.

Included Data Fields

• Company Name
• Technol...

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

National Coverage. Sample excludes the states of Chin, Kachin, and Kayah. The excluded areas represent less than 5% of the population.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Triennial

Sampling procedure

As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size in Myanmar was 1,020 individuals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.

Constrained estimates, total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. The mapping approach is Random Forest-based dasymetric redistribution.

More information can be found in the Release Statement

The difference between constrained and unconstrained is explained on this page: https://www.worldpop.org/methods/top_down_constrained_vs_unconstrained

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

Economic growth is central to economic development. When national income grows, real people benefit. While there is no known formula for stimulating economic growth, data can help policy-makers better understand their countries' economic situations and guide any work toward improvement. Data here covers measures of economic growth, such as gross domestic product (GDP) and gross national income (GNI). It also includes indicators representing factors known to be relevant to economic growth, such as capital stock, employment, investment, savings, consumption, government spending, imports, and exports.

This report details population and socioeconomic statistics of Gwa township. This report is a series of Township level reports published as part of the 2014 Population and Housing Census.The 2014 Population and Housing Census - the country’s first national census in 30 years – was undertaken by the Ministry of Immigration and Population with technical support from UNFPA between 30th March and 10th April 2014. 110,000 enumerators visited over 12 million households to gather data to provide social, economic and demographic characteristics of people and households for the purpose of on-going reforms, development planning and good governance. The results will be made public progressively as each stage of analysis is completed. Further information is available through http://www.dop.gov.mm/moip/ and http://countryoffice.unfpa.org/myanmar/census/

This report details population and socioeconomic statistics of Kungyangon township. This report is a series of Township level reports published as part of the 2014 Population and Housing Census.The 2014 Population and Housing Census - the country’s first national census in 30 years – was undertaken by the Ministry of Immigration and Population with technical support from UNFPA between 30th March and 10th April 2014. 110,000 enumerators visited over 12 million households to gather data to provide social, economic and demographic characteristics of people and households for the purpose of on-going reforms, development planning and good governance. The results will be made public progressively as each stage of analysis is completed. Further information is available through http://www.dop.gov.mm/moip/ and http://countryoffice.unfpa.org/myanmar/census/

📖 Arabic-Myanmar Quran Voice Dataset

  🕌 Overview

This dataset contains high-quality MP3 audio recordings of the entire Holy Qur’an with:

Arabic recitation of each verse Followed immediately by its Myanmar (Burmese) translation

It is the first complete Arabic-Myanmar Quran audio interpretation of its kind publicly released in Myanmar. The goal is to make the Qur’an more accessible to:

Elderly persons Blind or visually impaired people Myanmar speakers who wish to… See the full description on the dataset page: https://huggingface.co/datasets/freococo/arabic_myanmar_quran_voices.

Myanmar recorded 19434 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, Myanmar reported 637483 Coronavirus Cases. This dataset includes a chart with historical data for Myanmar Coronavirus Deaths.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Myanmar is 1000.

Mode of data collection

Mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

Sample excludes Chin, Kachin, and Kayahstates, representing less than 5% of thepopulation.

Analysis unit

Individuals

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Observation data/ratings [obs]

Sampling procedure

The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world's population (see Table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size was 1600.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

This report details population and socioeconomic statistics of Waw township. This report is a series of Township level reports published as part of the 2014 Population and Housing Census.The 2014 Population and Housing Census - the country’s first national census in 30 years – was undertaken by the Ministry of Immigration and Population with technical support from UNFPA between 30th March and 10th April 2014. 110,000 enumerators visited over 12 million households to gather data to provide social, economic and demographic characteristics of people and households for the purpose of on-going reforms, development planning and good governance. The results will be made public progressively as each stage of analysis is completed. Further information is available through http://www.dop.gov.mm/moip/ and http://countryoffice.unfpa.org/myanmar/census/

The number of COVID-19 vaccination doses administered per 100 people in Myanmar rose to 119 as of Oct 27 2023. This dataset includes a chart with historical data for Myanmar Coronavirus Vaccination Rate.

This report details population and socioeconomic statistics of Nanyun township. This report is a series of Township level reports published as part of the 2014 Population and Housing Census.The 2014 Population and Housing Census - the country’s first national census in 30 years – was undertaken by the Ministry of Immigration and Population with technical support from UNFPA between 30th March and 10th April 2014. 110,000 enumerators visited over 12 million households to gather data to provide social, economic and demographic characteristics of people and households for the purpose of on-going reforms, development planning and good governance. The results will be made public progressively as each stage of analysis is completed. Further information is available through http://www.dop.gov.mm/moip/ and http://countryoffice.unfpa.org/myanmar/census/

This report details population and socioeconomic statistics of Kalay township. This report is a series of Township level reports published as part of the 2014 Population and Housing Census.The 2014 Population and Housing Census - the country’s first national census in 30 years – was undertaken by the Ministry of Immigration and Population with technical support from UNFPA between 30th March and 10th April 2014. 110,000 enumerators visited over 12 million households to gather data to provide social, economic and demographic characteristics of people and households for the purpose of on-going reforms, development planning and good governance. The results will be made public progressively as each stage of analysis is completed. Further information is available through http://www.dop.gov.mm/moip/ and http://countryoffice.unfpa.org/myanmar/census/