This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions There will be an estimated 181 million new cancer cases (170 million excluding nonmelanoma skin cancer) and 96 million cancer deaths (95 million excluding nonmelanoma skin cancer) in 2018 In both sexes combined, lung cancer is the most commonly diagnosed cancer (116% of the total cases) and the leading cause of cancer death (184% of the total cancer deaths), closely followed by female breast cancer (116%), prostate cancer (71%), and colorectal cancer (61%) for incidence and colorectal cancer (92%), stomach cancer (82%), and liver cancer (82%) for mortality Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality) Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts CA: A Cancer Journal for Clinicians 2018;0:1-31 © 2018 American Cancer Society

https://acsjournals.onlinelibrary.wiley.com/doi/epdf/10.3322/caac.21492

Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.

https://acsjournals.onlinelibrary.wiley.com/doi/pdf/10.3322/caac.21660

Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.

Cancer constitutes an enormous burden on society in more and less economically developed countries alike. The occurrence of cancer is increasing because of the growth and aging of the population, as well as an increasing prevalence of established risk factors such as smoking, overweight, physical inactivity, and changing reproductive patterns associated with urbanization and economic development. Based on GLOBOCAN estimates, about 14.1 million new cancer cases and 8.2 million deaths occurred in 2012 worldwide. Over the years, the burden has shifted to less developed countries, which currently account for about 57% of cases and 65% of cancer deaths worldwide. Lung cancer is the leading cause of cancer death among males in both more and less developed countries, and has surpassed breast cancer as the leading cause of cancer death among females in more developed countries; breast cancer remains the leading cause of cancer death among females in less developed countries. Other leading causes of cancer death in more developed countries include colorectal cancer among males and females and prostate cancer among males. In less developed countries, liver and stomach cancer among males and cervical cancer among females are also leading causes of cancer death. Although incidence rates for all cancers combined are nearly twice as high in more developed than in less developed countries in both males and females, mortality rates are only 8% to 15% higher in more developed countries. This disparity reflects regional differences in the mix of cancers, which is affected by risk factors and detection practices, and/or the availability of treatment. Risk factors associated with the leading causes of cancer death include tobacco use (lung, colorectal, stomach, and liver cancer), overweight/obesity and physical inactivity (breast and colorectal cancer), and infection (liver, stomach, and cervical cancer). A substantial portion of cancer cases and deaths could be prevented by broadly applying effective prevention measures, such as tobacco control, vaccination, and the use of early detection tests.

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Global cancer statistics, 2012

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(12)61728-0.pdf

Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010

Chapter 64. General Primary Care

BackgroundUnderstanding vaccination hesitancy during early vaccination rollout in Canada can help the governments vaccination efforts in education and outreach, which may help eventually achieving herd immunity. This study uses an online survey to assess vaccination hesitancy in population subgroups in Canada. MethodPanel members from the nationally representative Angus Reid Forum were randomly invited to complete an online survey on their experiencing with COVID-19 symptoms and testing, as well as intention to vaccination against COVID-19. Respondents were asked "when a vaccine against the coronavirus becomes available to you, will you get vaccinated or not?" Vaccination hesitancy was defined as choosing "No - I will not get a coronavirus vaccination" as a response. Results14,621 panel members (46% male and 53% female) completed the survey. Although the respondents overrepresent age 60+ and higher levels of education, other demographics, the prevalences of smoking, obesity, diabetes and hypertension were comparable to the Canadian national census and health surveys. COVID-19 vaccination hesitancy is relatively low overall (9%). Being a resident of Alberta (predicted probability = 15%), aged 40-59 (OR = 0.87, 0.78 - 0.97, predicted probability = 12%), identifying as a visible minority (OR = 0.56, 0.37 - 0.84, predicted probability = 15%), having some college level education or lower (predicted probability = 14%), or living in households of at least 5 are related to greater vaccination hesitancy (OR = 0.82, 0.76 - 0.88, predicted probability = 13%). ConclusionOur study enhances the understanding of COVID-19 vaccination hesitancy and identifies key population groups with higher vaccination hesitancy. As the Canadian COVID-19 vaccination effort continues, policymakers may focus outreach, education, and other efforts on these groups, which also represent groups with higher risks for contracting and dying from COVID-19. Furthermore, Canada would need to vaccinate virtually the entire population to reach herd immunity due to its relatively low infection level, and a high vaccination hesitancy would be a major hurdle to achieving that.

/pdf/quantifying-covid-19-vaccination-hesitancy-during-early-5frg72lg7w.pdf

Quantifying COVID-19 vaccination hesitancy during early vaccination rollout in Canada

La mortalité du rotavirus en Inde: Estimations fondáes sur une enquête nationale représentative des décés par diarrheáe

Sex ratio in India. Authors reply [letter]

We thank Edward Mills for pointing out, in response to our article on India's HIV-1 epidemic,[1][1] that men who have sex with men (MSM) are contributing to the HIV-1 epidemic in India. We think there are similarities between MSM and commercial sex workers, but also important differences.

In Andhra

/pdf/more-on-india-s-hiv-1-epidemic-127f8aab2t.pdf

Prabhat Jha

Papers

Chapter 64. General Primary Care

Quantifying COVID-19 vaccination hesitancy during early vaccination rollout in Canada

La mortalité du rotavirus en Inde: Estimations fondáes sur une enquête nationale représentative des décés par diarrheáe

Sex ratio in India. Authors reply [letter]

More on India's HIV-1 epidemic