A pandemic called COVID-19 swap the whole the planet during 2020. Many countries suffered from that. Although there are some countries like China, South Korea which have the ability to control the pandemic or reduce its effects powerfully, there are still other countries which have severe pandemic situations such as India and Brazil. Seven countries are selected to be compared. Within the comparison, we may have a little glance of how this disease affected one third of the population of the planet and how human beings are responding to it. Our report starts from this disaster and explores how it rages around the world. We also care about how governments respond to it and how these responses could influence the situation in return. Also, countries are always with their own uniqueness, these unique properties could also lead to various situations. Exploring how their characteristics such as cultural, socio-economic influence the Covid-19 Pandemic for these countries may reveal the mystery under the circumstance of Covid-19 pandemic and provide some clues for future research about how to better respond to similar disasters.
All these 7 countries are being through a hard time from the pandemic, but the governments’ responses vary from each other. Some are quite motivative, while others are not. Motivative governments are always prepared, they would like to post all kinds of methods to deal with the pandemic. Also, they respond quickly. As long as the situation changes, they correspond it with updated measures. God help those who help themselves. Countries own low confirmed cases and low death rate, while some countries do not possess this luck.
The chart below shows different confirmed cases among 7 countries and here comes our analysis.
For the figure of the total number of covid-19 confirmed cases in seven countries over time, Brazil is found which had the most confirmed cases from May,2020 to August,2020, and then India exceeded Brazil at the beginning of September,2020. Other 5 countries have much less confirmed cases than these two countries. The Covid-19 confirmed case increase rate for Brazil began to slow down during August,2020. When India exceeded Brazil, its increase rate of Covid-19 confirmed cases was still increasing. Up to October 2020, India still had the high confirmed rate. Sri Lanka had slowest increase in number of Covid-19 confirmed case over time. Pakistan, Indonesia, and Bangladesh also had a slow increase in total number of Covid-19 confirmed cases
Next, number of covid-19 death case for these seven countries over time are explored.
For the figure for situations of covid-19 death cases, Brazil has the most death number compared to other countries. India has the second most death number compared to other five countries. Sri Lanka, Pakistan, Indonesia, and Bangladesh also had a slow increase in total number of Covid-19 death cases.
After analyzing these covid-19 confirmed cases trends and covid-19 death cases, there are some findings. First, before 6th, September,2020, Brazil had the greatest number of Covid-19 confirmed cases. Then, India had the most covid-19 confirmed cases after 6th, September,2020. However, India always had less death number of covid-19 than Brazil which always had the greatest number of covid-19 death case. Other five countries have much less covid-19 confirmed cases.
However, it’s important to notice that proportions for covid-19 confirmed cases and death cases in each country need to be analyzed to judge whether situations of covid-19 confirmed cases and death cases are correlated to each country’s population. Also, after looking at proportions of covid-19 cases, government measures will be analyzed to explore their responses in controlling this pandemic and compare them to actual covid-19 cases trends to explore different results of responses and possible reasons why there exists different results in different country.
In order to have a better comparsion for seven countries Covid-19 cases, a bar chart for total number of covid-19 confirmed casese, death and recovery is plotted.
From the bar chart to show number of covid-19 cases, it’s clearer to observe the final situations for all countries compared to timeline charts for number of covid-19 cases which plotted before. It shows the same conclusions as line charts for covid-19 confirmed cases and death cases. India has the most covid-19 confirmed cases and Brazil has the second most covid-19 confirmed cases. Bangladesh has the third most covid-19 confirmed cases, Indonesia has the fourth most covid-19 confirmed cases. Pakistan has the fifth most covide-19 confirmed cases. Sri Lanka has the least covide-19 confirmed cases.
Next, the proportions of covid-19 confirmed cases, death cases and recovery in each country’s population is shown in the bar chart below.
From the figure for proportion of covid-19 cases in each country’s own population, it is easily to find a difference between proportion chart and total number chart that Brazil has the largest proportion for covid-19 confirmed case. Other countries have the similar situations as the figure for total number of covid-19 shows. Therefore, although India has the most covid-19 confirmed cases, Brazil has the largest proportion for coivid-19 confirmed case number in its population.
After exploring trends for covid-19 cases, Government measures are used to further illustrate responses of these countries and explore why there were different results.
Firstly, number of government’s measures for seven countries is analyzed by looking at different measure’s categories.
For the bar chart for government measures with different categories, Sri Lanka has the most measures in governance and socio-economics measures, movement restrictions, public health measures and social distancing measures. It explains why it has the least covid-19 confirmed cases and death cases and smallest proportion of covid-19 cases in its population. Additionally, compared Brazil and India, it is easy to find that India has more public health measures. It might be the reason why India has less death cases and smaller death proportion in its population. However, although India has similar number of movement restriction measures as Brazil, India has more confirmed cases than brazil. The reason might be that it has half less social distancing measures compared to Brazil. Another important finding is that lockdown measures have no obvious correlation to situation of covid-19 in different countries. However, Social distancing played a possible positive role in controlling the pandemic. The reason can be found from the comparison of Brazil and India and from the whole situation for countries’ social distancing number order.
In order to having a further look at how government measures change over time, seven countries’ numbers of government measures for each day are shown as the following line charts.
From the line chart for Sri Lanka’s government measures count over time, government announced measures frequently and had the greatest total measure number. The efficient implementation of measures played an important role in controlling Covid-19 confirmed and death cases to the least one among seven countries.
From the line chart for Egypt’s government measures count over time, it has less frequent announcement of government’s measures than Sri Lanka. From the situation of Covid-19 cases, the implementation of government’s measures is efficient. Less frequent measures and lese total measures are possible reasons to lead to the more Covid-19 cases than Sri Lanka.
From the line chart for Pakistan’s government measures count over time, it has similar frequency and number for announcement of government’s measures as Egypt. From the situation of Covid-19 cases, Pakistan has the fifth most covide-19 confirmed cases. The implementation of government’s measures is efficient. Less frequent measures and lese total measures are possible reasons to lead to the more Covid-19 cases than Sri Lanka.
From the line chart for Indonesia’s government measures count over time, it has less frequency for announcement of government’s measures as Pakistan. It has more number to announce in a day. From the situation of Covid-19 cases, Indonesia has the fourth most covid-19 confirmed cases. However, the number of Covid-19 cases is not too large. Therefore, the implementation of government’s measures is efficient. Less frequent measures and lese total measures are possible reasons to lead to the more Covid-19 cases than Sri Lanka.
From the line chart for Bangladesh’s government measures count over time, it has less frequent announcement of government measures compared to Pakistan, Indonesia, Egypt, and Sri Lanka. The implement of announcement of government measures might be efficient. However, Bangladesh can increase frequency and numbers of measures to improve the control for Covid-19.
From the line chart for India’s government measures count over time, government started to make measures from 8th, January,2020. Then It began to make frequent measures. From March to August, the number of measures in a day follows a trend to reduce frequency and number of declaring measures. However, from the line chart that shows total Covid-19 confirmed cases overtime, India’s increase rate of covid-19 confirmed cases increased over time and still was high in October. Therefore, it shows government measures of India did not catch up with change of Covid-19 confirmed cases.
From the line chart for Brazil’s government measures count over time, Brail government made frequent measures from March to May 2020. However, Brazil had the most Covid-19 cases before September 2020. It means that Brazil government measures did not play a great role in controlling Covid-19 initially.
However, its increase rate for Covid-19 confirmed cases slowed down in August,2020. It means the recent measure before August might make a role in controlling Covid-19 confirmed cases. In conclusion, the announcement and implementation of government measures did not play a good role in controlling Covid-19 pandemic.
In conclusion, the implementation of government measures for India is not efficient to control the Covid-19. India also did not regulate its measures to adopt the change of Covid-19 situation. The frequency of government measures for Brazil is not high and the implementation of government measures for Brazil did not play a great role in controlling Covid-19 cases. Sri Lanka announced government’s measures frequently and largely and has an efficient implementation for government’s measures. For other countries, the frequency and number of measures have a positive correlation to control Covid-19 Pandemic.
Different categorical measures played different roles in controlling Covid-19 Pandemic. Public health measure might can reduce death cases of Covid-19. Movement restriction and social distancing played important roles in controlling Covid-19 confirmed cases.
The horrible monster COVID-19 does not only cause sickness and deaths. It harms people financially. To take the situation under control, governments try to keep people away from getting together, but at the same time, that means a lot of people cannot go to work anymore. As a result, GDP drops. Facing this situation, what are these 7 governments’ responses to it and how are they going to deal with this cold winter in the field of economy?
COVID-19 Pandemic has different economic impacts on the countries like India, Sri Lanka, Bangladesh, Pakistan, Brazil, Egypt and Indonesia, which can be demonstrated from the varying degree of changes in each country’s GDP as well as unemployment rate during the Pandemic. First, let us have a look at each country’s unemployment rate to see how jobs are being lost worldwide.
With data from Trading Economics (2020), here comes the line chart of quarterly unemployment rate (%) for India, Sri Lanka, Egypt, Indonesia and Brazil.
We can see that all countries’ unemployment rate had risen after Q1 2020 except Indonesia (purple line). And among these countries, India (dark blue line) had the most obvious increase in unemployment rate from Q1 2020 to Q2 2020, then came Egypt (green line) and Brazil (orange line). For Sri Lanka, even though there was no data after Q1 2020, it could be seen that it had the tendency of an increasing unemployment rate.
Now, we had a basic idea about the condition of job losing in each 5 countries, it is a good time to look at how each country’ economic being influenced during the Pandemic.
With data from Trading Economics (2020), here comes the line chart of quarterly GDP growth rate (%) for India, Sri Lanka, Egypt, Indonesia and Brazil.
It shows that most countries’ economy started to or had a tendency to shrink in and after Q1 2020 (the time around when the Pandemic began). Among these countries, India (blue line) seemed to have the most badly hurt economy with a rapid decline of GDP growth rate from 0.7 in Q1 2020 to -25.2 in Q2 2020. And for Indonesia (purple line) and Brazil (orange line), even though their economy was not attacked as severely as India’s, they were already or started being under a negative GDP growth rate in Q1 2020, and an obvious further decrease in GDP growth rate can be seen for both of them from Q1 2020 to Q2 2020. For Sri Lanka (red line), even though we do not have the GDP growth rate after Q1 2020, we can still tell that with a positive rate from 2 in Q4 2019 to a negative one -1.6 in Q1 2020, Sri Lanka’s economy displayed a contraction when reached Q1 2020. And for Egypt (green line), it is hard to tell what its economy would look like after Q1 2020, and it seemed like there was no big turbulence in Egypt’s economy: only a little decrease of rate from 5.6 in Q4 2019 to 5 in Q1 2020 for Egypt’s economy, and in that it still kept a positive growth rate of 5 in Q1 2020, there was no sign of a decrease in its GDP.
To study the economy of Bangladesh and Pakistan during the Pandemic, yearly GDP that was predicted and computed based on current situation, provided by International Monetary Fund (2020), was used to see how these two countries’ economy would be affected. Here comes 2 line charts of Yearly GDP: one for Bangladesh and Pakistan only and one for all 7 countries to compare the varying seriousness of each 7 countries’ economy shocks. First, look at the line chart for Bangladesh and Pakistan’s Yearly GDP.
For Pakistan (red line), it is not able to know how its economy would be affected during the Pandemic since no data is available now for its yearly GDP, even the predicted one, in 2020 or any further years, even though it did show the tendency of a decreasing GDP for year 2019. And for Bangladesh (blue line), it can be seen that even though it would keep having an increasing GDP, when it came to the year 2020, the growth rate of GDP would decrease (the slope of the line went flatter) and this growth rate would barely change until around the year 2021. Which means the economy of Bangladesh would still grow but would grow slowly after 2020.
Now, have a look at to what degree would the economy of Pakistan and Bangladesh, or just Bangladesh, be affected when being compared among all 7 countries.
Here is the line chart for all 7 countries’ Yearly GDP.
We can see that when putting Yearly GDP of Bangladesh and Pakistan in all the 7 countries’, these two countries (purple line and orange line) would not be affected as obviously as India (dark blue line) or Brazil (light blue line) which showed an obvious decline of GDP in the year 2020.
With above information, we can conclude that:
India and Brazil are the two countries confronted with severe economy decreasing. And for Indonesia and Sri Lanka, although they also have a decrease in GDP but the situation is not as bad as India and Brazil. For Bangladesh and Egypt, although their GDP is still increasing but the increasing rate slows down. Last, for Pakistan, it would be hard to tell since data for 2020 is still not published.
Facing different degrees of economic shocks, each country applied different economic measures to mitigate the shocks. Below information was provided by ACAPS (2020).
India implemented several economic measures from 3/15/2020 to 8/19/2020, which included “Deploy fiscal resources for additional medical facilities, central instruct state government”, “Relief Package towards responsive Governance in Challenging Times Which Will Provide Relief to Vulnerable Sections”, “Govt gives benefits to farmers on crop loan repayments due to Covid-19 lockdown”, “CBDT issues orders u/s 119 of IT Act,1961 to mitigate hardships to taxpayers arising out of compliance of TDS/TCS provisions”, “Amends the extant FDI policy for curbing opportunistic takeovers/acquisitions of Indian companies due to the current COVID-19 pandemic”, “$1.5 billion loan to support government's response to COVID-19 pandemic”, “Government of India & AIIB sign an Agreement for $750 Million for COVID-19 support for India” and “RBI provides additional monetary support to housing, rural and priority sectors”.
Sri Lankaimplemented several economic measures from 3/19/2020 to 7/25/2020, which included “Sri Lanka SEC to grant relief to investors affected by the COVID-19 hit market”, “Sri Lankan Airlines implements cost-saving measures to ensure its survival, livelihoods of employees”, “Low income vulnerable families have been granted a host of financial and material benefits in the face of the COVID-19 outbreak”, “Sri Lanka introduces tax-free deposit account to attract foreign currency”, “Sri Lanka government re-introduces abolished taxes”. “Government purchases over 900,000 kilos of vegetables from farmers” and “Extension of the agreed period regarding the private sector salary payment in the crisis caused by the Covid-19 Epidemic”.
Bangladesh implemented economic measure of “Targeting Covid-19 Relief Payments” in 5/8/2020
Pakistan implemented several economic measures from 3/19/2020 to 5/21/2020, which included “Economic intervention to safeguard national economy from adverse impacts of corona pandemic. This includes actively coordinating for necessary emergency funds to ward off negative impacts on industry”, “A massive 1.2 trillion-rupee relief package announced by the Federal government will be distributed among all provinces without any discrimination”, “Web portal for financial support of unemployed due to Covid-19” and “6 million category-4 beneficiaries under Ehsaas Emergency Cash channeled through PM-COVID19 funds”.
Brazil implemented several economic measures from 4/3/2020 to 5/29/2020, which included “Tax exemptions on medicines and medical supplies were granted, while the pharmaceutical industry agreed to suspend the annual increase of medicines for two months” and “Bill passed by the Federal Senate earlier to provide some income for the poorest, unemployed and workers in the informal economy with no fixed income, as well as states and municipalities to combat the COVID-19”.
Egypt implemented several economic measures from 3/17/2020 to 8/17/2020, which included “The Central Bank of Egypt announced a temporary daily cash withdrawal limits of 10,000 Egyptian pounds (USD 636) for individuals and 50,000 Egyptian pounds (USD 3184) for companies. ATM withdrawals are capped at 5000 Egyptian pounds (USD 318). The bank also encouraged the use of digital bank transfers and electronic payments to reduce contact and exposure. Associated fees have been waived” and “The Egyptian authorities are carrying out a number of national megaprojects to increase aggregate demand and create jobs”.
Indonesia implemented several economic measures from 5/6/2020 to 7/20/2020, which included “APEC economies agree to keep markets open and trade flowing”, “The Government of Indonesia has announced a fund allocation of IDR. 695.2 trillion to mitigate the impact of the COVID19 pandemic, which includes IDR. 203.9 trillion for social assistance” and “The Coordinating Ministry for Economic Affairs plans to re-start its pre-employment training program by opening a fourth batch of trainings by the end of July”.
All 7 countries had taken various economic measures during different time in 2020. To see if these measures had worked, 2 variables were used and treated as indicators here to show where the economy was headed: Workplace closing index and Income support index. These two indices could be found from the Research projects web page of the Blavatnik School of Government in University of Oxford (2020). Closing workplace could have a huge impact on economic in that it would bring a reduction in the number of working people, and if there were more workplaces being closed, it would mean more people would take time off the work, and the economy might be being through a worse condition. And income support, which is used for helping people on a low income, could imply how bad the economic was since if there was more income support needed, it would mean more people were under a low income and the economy was in a worse condition.
Based on above description and under the case that no governments among these countries were closing workplaces to force the economy ticking, changes in workplaces closing and income support before and after economic measures being applied could indicate and help us to learn how economy would change after economic measures being implemented. Here comes 2 line plots for the workplace closing index and income support index during the year 2020. The indices would show at what scale the workplace was closed or the income support was granted.
It can be shown from the line plot for the workplace closing index that most countries started to close their workplaces in March, the time around when the Pandemic arrived, and there was a drop in the scale of workplace closing for each country around the month June, the time when several measures were and being applied. And for Sri Lanka (green line), it had the most obvious drop in scale in June, then were India (dark blue line) and Bangladesh (purple line), and then were Brazil (light blue line), Indonesia (red line) and Pakistan (orange line). For Egypt (pink line), there was no change in scale from March to October. From the line plot of income support index, we can see that most countries started to provide income support around March and April, the time around when the Pandemic arrived, and it seemed like most countries (without data for Sri Lanka) were still keeping the scale of income support through the time, while India (dark blue line) and Bangladesh (purple line) had a drop in scale in September and May respectively.
So, we can conclude that:
Based on what workplace closing index and income support index indicated, it could be possible that the economy of India and Bangladesh was relived to the most extent after the economic measures was implemented, and then came Brazil, Indonesia and Pakistan. For Egypt, the economy might have not shown a relief yet. Last, for Sri Lanka, even though it showed an obvious drop in the number of workplace closing, but more data is needed to learn about its economy situation.
In this report, we have seven countries, which means, they can be very different from each other. They have different religions, different cultures, as well as different average education levels. So how can these factors play a role in the consequence of COVID- 19 among the 7 countries, and do they really make a difference? With data representing the cultural, socio-economic, and topographic characteristics of seven countries, we are determined to find out the answer.
In order to analyze possible roles of socio-economic, topographical and cultural characteristics in the Covid-19 pandemic. Socio-economic status score is used to represent socio-economic characteristic. Population density is used to represent topographical characteristic. Country’s composition of religions is used to represent cultural characteristic.
Firstly, a bar chart for each country’s socio-economic status score is shown to explore the role of socio-economic characteristic in the Covid-19 pandemic.
For the bar chart for socio-economic status (2010), Sri Lanka has the largest score, Brazil, Egypt, and Indonesia have the second, third and fourth largest score. India, Bangladesh, and Pakistan have the similar small score compared with other countries.
From comparison of socio-economic status for seven countries and their covid-19 cases, most high socio-economic status score’s countries have less severe Covid-19 pandemic situations. Most low socio-economic status score’s countries have more severe Covid-19 pandemic situations. Two exceptions are Brazil and India. Therefore, these two countries might have other factors to affect their trend for Covid-19 Pandemic. For other five countries, socio-economic status score has a negative correlation with spread of Covid-19 pandemic. Higher socio-economic status score has a better ability to control Covid-19 Pandemic. Additionally, although a previous finding is that India declared a lot of government measures in movement constriction and social distancing, India did not control Covid-19 confirmed cases trends as other countries. The possible reason is that India has a low socio-economic status score.
Next, a bar chart for population density of each country is shown to explore the role topographic characteristic in Covid-19 pandemic.
From the comparison of population density for seven countries and Covid-19 cases of seven countries, population density did not play an obvious role in the covid-19 pandemic. The reasons are illustrated as follows. Firstly, Bangladesh has the largest population density, but it has less Covid-19 confirmed case number compared to other 6 countries. India has the second population density among seven countries, but it has the second most covid-19 confirmed case number. Brazil has the smallest population density among seven countries, but it has the second most confirmed case number. Therefore, the population density did not play an obvious role in the spread of covid-19 pandemic.
Lastly, each country’s religion composition is shown in the bar chart below.
For cultural characteristics, religions composition for each country’s population is shown in the upper left figure. For most countries, they all have a predominant religion except Brazil. Since Brazil violates the possible trend for socio-economic status scores to affect Covid-19 confirmed cases. Also, it had declared a lot of measures. The possible reason is that Brazil has multiple main religions. Lastly, compared with total covid-19 cases distribution, there are no obvious general relationship between variety of religions in a country and situation of covid-19 pandemic in a country.
Summarily, socio-economic status might have a negative correlation with Covid-19 confirmed cases. Population density does not play an obvious role in the Covid-19 pandemic. The Religion’s proportion in country’s population might explain the violation of Brazil to follow the correlation between socio-economic status and Covid-19 confirmed cases. The reason might be that Brazil has multiple main religions instead of one predominant religion for one country.
Situations also vary within groups of different properties. For instance, women and men, how people with different gender are influenced in COVID-19? It seems that different genders have different death rates among these countries.
Covid-19 has impacted people with different genders from the perspectives of unemployment rate as well as confirmed cased and death counts. To see how different genders being affected in different ways, the unemployment rate and confirmed Covid-19 cases and deaths counts during the Pandemic within and between countries would be studied here.
With data from The World Bank (2020) and Global Health 5050 (2020), here comes 2 line plots for female and male unemployment rate, 2 bar charts for cases and deaths counts based on gender and 2 pie charts for the ratio of female and male cases and deaths in Bangladesh.
First, having a look at how unemployment rate of female and male would change during the Pandemic in each country.
Looking through each year’s female and male unemployment rate for each country, it can be demonstrated that Egypt (pink line) and Brazil (light blue line) always had the highest female and male unemployment rate, and then came other countries. And among these countries, it seemed like there was no big difference in change in each country’s female and male unemployment rate from the year 2019 to 2020, which might indicate that female and male might be influenced in the similar way from the respective of unemployment rate -- both had no big change -- within and among 7 countries during the Pandemic.
Having looked at the change in unemployment rate for different genders, we can also have a look at how differently females and males could be impacted by Covid-19. Here comes 2 bar charts indicating the ratio of female and male in Covid-19 confirmed cases and deaths for India, Sri Lanka, Bangladesh, Pakistan and Brazil.
We can see that for Covid-19 confirmed cases, India, Sri Lanka and Bangladesh all had their males much more than females being tested positive, and Brazil had nearly the same amount of males and females being confirmed of Covid-19. Pakistan was the only country having females more than males, even though the difference between genders was not as much as the differences between genders in India, Sri Lanka and Bangladesh, being in confirmed cases.
For Covid-19 death counts, all the 5 countries had their males more than females in deaths. Among these countries, Sri Lanka had the biggest variance in death counts between two genders, then came Bangladesh, and then was India, and last were Pakistan and Brazil.
So, we can conclude that:
Bangladesh, India and Sri Lanka showed the most obvious difference between two genders when it came to Covid-19 confirmed cases and death counts. And they all had much more males than females being attacked by the pandemic. For Pakistan and Brazil, the difference between genders was less obvious in the perspective of Covid-19 confirmed cases and death counts. For Indonesia and Egypt, it would be hard to say since there was no data for their gender related Covid-19 cases and death counts.
To see more specifically how people with different genders being involved in Covid-19 within a country, Bangladesh, which had the most obvious difference between two genders for Covid-19 confirmed cases and deaths, would be studied here. For this, here comes 2 pie charts showing exact ratio of males and female in confirmed cases and deaths.
It can be shown that in Bangladesh, nearly 3/4 of total confirmed cases were males and more than 3/4 of total deaths were males. Which indicated that much more males than females in Bangladesh would be affected by Covid-19.
For the disease itself, the number of confirmed cases and death cases for different countries vary. This is partly because of the quantity, frequency and effectiveness difference of the government methods in difference countries. For example, the implementation of government measures for India is not efficient to control the Covid-19. Sri Lanka announced government’s measures frequently and largely and has an efficient implementation for government’s measures. The question also concerning the reaction speed of government (whether increase methods if more confirmed cases domestically) towards the situation also vary. For example, Brazil government announced quite a lot methods in April. But it failed to implement and announce more effective methods to deal with the increasing rate of confirmed cases in the country. Other factors contributing to the difference includes the socio-economic status index, po. For a country with a high index like Sri Lanka, higher education level and salary, and their occupations distribution have a negative correlation with the confirmed cases.
Countries also suffer from Covid-19 in economy differently. The economy of India and Brazil suffers from covid-19 severely. Indonesia and Sri Lanka also suffers a decreasing in GDP. The pandemic slows down the GDP increasing in Bangladesh and Egypt. Governments also published several methods to motivate the economy recovery. Although there is no direct evidence to indicate the economy has been recovered or the decreasing rate has been alleviated. But more working places have been opened and families are with less income support may imply that the situation is getting better.
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