Excess mortality in low-and lower-middle-income countries: A systematic review and meta-analysis (preprint)

Background: The COVID-19 pandemic caused a massive death toll, but its effect on mortality remains uncertain in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality in LLMICs, including methods, data sources, and factors that might have influenced excess mortality. Methods: The protocol was registered in PROSPERO (ID: CRD42022378267). We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus for studies conducted in LLMICs on excess mortality. These included studies with at least a one-year non-COVID-19 period as the comparator in estimating excess mortality and with publication dates from 2019 to date. The meta-analysis included studies with extractable data on excess mortality, methods, population size, and observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio of excess mortality with 95% confidence intervals. Results: The review included studies from 29 countries, of which 10 were included in the meta-analysis. Of 1,405,128,717 individuals, 2,152,474 deaths were expected, and 3,555,880 deaths were reported. The pooled excess mortality was 100.3 deaths per 100,000 population per pandemic period. The excess risk of death was 1.65 (95% CI: 1.649, 1.655 p<0.001). Data sources included civil registration systems, obituary notifications, surveys, public cemeteries, funeral counts, burial site imaging, and demographic surveillance systems. Techniques used to estimate excess mortality were mainly statistical forecast modelling and geospatial analysis. Of the 24 studies, only one found higher excess mortality in urban settings. Conclusion: Our results show that excess mortality in LLMICs during the pandemic was substantial. There is uncertainty around excess mortality estimates given comparatively weak data. Further studies are needed to identify the drivers of excess mortality by exploring different methods and data sources.

Access to healthcare as an important moderating variable for understanding geography of immunity levels for COVID-19 - preliminary insights from Poland (preprint)

BackgroundUnderascertainment of COVID-19 burden and uncertainty in estimation of immunity levels is a known and common phenomenon in infectious diseases. We tested to what extent healthcare access (HCA) related supply/demand interfered with registered data on COVID-19 from Poland. Material and methodsWe have run a multiple linear regressions model with interactions to explain geographical variability in seroprevalence, hospitalization (on voivodeship -NUTS-2- level) and current (beginning of the 4th wave -15.09-21.11.2021) case notifications/crude mortality (on poviats -old NUTS-4- level) taking vaccination coverage and cumulative case notifications till so called 3rd wave as predictor variables and supply/demand (HCA) as moderating variables. ResultsHCA with interacting terms (mainly demand) explained to the great extent the variance of current incidence and most variance in case of current mortality. HCA (mainly supply) is significantly moderating cumulative case notifications till the 3rd wave explaining the variance across seroprevalence. ConclusionsSeeking causal relations between vaccination or infection gained immunity level and current infection dynamics could be misleading without understanding socio-epidemiological context such as the moderating role of HCA (sensu lato). After quantification, HCA could be incorporated into epidemiological models for better prediction of real disease burden.

Mild Adverse Events of Sputnik V Vaccine Extracted from Russian Language Telegram Posts via BERT Deep Learning Model (preprint)

Background: There is a limited amount of data on the COVID-19 vector vaccine Gam-COVID-Vac (Sputnik V) safety profile. Previous infodemiology studies showed that social media discourse could be analyzed to assess the most concerning adverse events (AE) caused by drugs. Objective: We aimed to investigate mild AEs of Sputnik V based on a participatory trial conducted on Telegram in the Russian language. We compared AEs extracted from Telegram with other limited databases on Sputnik V and other COVID-19 vaccines. We explored symptom co-occurrence patterns and determined how counts of administered doses, age, gender, and sequence of shots could confound the reporting of AEs. Materials and Methods: We collected a unique dataset consisting of 11,515 self-reported Sputnik V vaccine AEs posted on the Telegram group, and we utilized natural language processing methods to extract AEs. Specifically, we performed multi-label classifications using the deep neural language model BERT DeepPavlov, which we pre-trained on a Russian language corpus and applied to the Telegram messages. The resulting AUC score was 0.991. We chose symptom classes that represented the following AEs: fever, pain, chills, fatigue, nausea/vomiting, headache, insomnia, lymph node enlargement, erythema, pruritus, swelling, and diarrhea. Results: The results of the retrospective analysis showed that females reported more AEs than males (1.2-fold, P

Risk Perception of COVID-19 in the German Internet Media and its epidemiological consequences during first wave of infections - exploration of possible research topic (preprint)

Due to the spread of SARS-CoV-2 virus infection and COVID-19 disease, there is an urgent need to analyze epidemic perception in Germany. This would enable authorities for preparation of specific actions minimizing public health and economic risks. The aim of this article is to singal possible research activities for future research.The aim of this study is to quantitatively investigate perception of COVID-19 in German Media (Twitter, Google, Youtube and selection of news articles) in the Internet by infodemiological approach. We proposed quantitative Media analysis as Retrospective and for future Prospective observatory analysis of secondary data. We attempt to analyze main discourses via natural language processing tools (such as topic modelling and sentiment analysis), multilayer and temporal network analysis of accounts/words/topics and time series analysis.There were just a few previous works quantitatively linking Internet activities and risk perception of infectious diseases in Germany. Traditional and social media do not only reflect reality, but also create it. German authorities, having a reliable analysis of the perception of the problem, could optimally prepare and manage the social dimension of the epidemic.The analysis of electronic media makes it possible to analyze the problem perception in Germany and early detect possible behavioral changes (e.g. fear, anxiety) associated with the epidemic, which is crucial for a targeted response and tailored containment scenarios to minimize public health risks. Mistrust of governmental measures implementation has fulled Querdenken movement - an unlikely alliance of far-right and left-wing, as well as conspiracy theorists.Being aware of many shortcomings of computational/digital epidemiology and its exploratory approach, it provides us with an opportunity to analyze a huge amount of digital footprint data at low cost and in a short time.There is no confict of interest.

An attempt to optimize human resources allocation based on spatial diversity of COVID-19 cases in Poland (preprint)

Our task is to examine the relationship between the SARS-CoV-2 arrival and the number of confirmed COVID-19 cases in the first wave (period from March 4 to May 22, 2020 (unofficial data)), and socio-economic variables at the powiat (county) level (NUTS-4) using simple statistical techniques such as data visualization, correlation analysis, spatial clustering and multiple linear regression. We showed that immigration and the logarithm of general mobility is the best predictor of SARS-CoV-2 arrival times, while emigration, industrialization and air quality explain the most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution of human resources between poviats.

TRENDS IN PERCEPTION OF COVID-19 IN POLISH INTERNET (preprint)

INTRODUCTION: Due to the spread of SARS-CoV-2 virus responsible for COVID-19 disease, there is an urgent need to analyse COVID-19 epidemic perception in Poland. This study aims to investigate social perception of coronavirus in the Internet media during the epidemic. It is a signal report highlighting the main issues in public perception and medical commutation in real time. METHODS: We study the perception of COVID-19 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet on platforms: Google, Twitter, YouTube, Wikipedia and electronic media represented by Event Registry, from January 2020 to 29.04.2020 (before and after official introduction to Poland on 04.03.20). We present trend analysis with a support of natural language processing techniques. RESULTS: We identified seven temporal major clusters of interest on the topic COVID-19: 1) Chinese, 2) Italian, 3) Waiting, 4) Mitigations, 5) Social distancing and Lockdown, 6) Anti-crisis shield, 7) Restrictions releasing. There was an exponential increase of interest when the Polish government declared war against disease around 11/12.03.20 with a massive mitigation program. Later on, there was a decay in interest with additional phases related to social distancing and an anti-crisis legislation act with local peaks. We have found that declarations of mitigation strategies by the Polish prime minister or the minister of health gathered the highest attention of Internet users. So enacted or in force events do not affect interest to such extent. Traditional news agencies were ahead of social media (mainly Twitter) in dissemination of information. We have observed very weak or even negative correlations between a colloquial searching term antiviral mask in Google, encyclopaedic definition in Wikipedia SARS-CoV-2 as well official incidence series, implying different mechanisms governing the search for knowledge, panic related behaviour and actual risk of acquiring infection. CONCLUSIONS: Traditional and social media do not only reflect reality, but also create it. Risk perception in Poland is unrelated to actual physical risk of acquiring COVID-19. As traditional media are ahead of social media in time, we advise to choose traditional news media for a quick dissemination of information, however for a greater impact, social media should be used. Otherwise public information campaigns might have less impact on society than expected.

Trends in Perception of COVID-19 in Polish Internet (preprint)

Introduction: Due to the spread of SARS CoV-2 virus responsible for COVID-19 disease, there is an urgent need to analyse COVID-19 epidemic perception in Poland. This study aims to investigate social perception of coronavirus in the Internet media during the epidemic. It is a signal report highlighting the main issues in public perception and medical commutation in real time. Methods: We study the perception of COVID-19 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet on platforms: Google, Twitter, YouTube, Wikipedia and electronic media represented by Event Registry, from January 2020 to 29.04.2020 (before and after official introduction to Poland on 04.03.20). We present trend analysis with a support of natural language processing techniques. Results: We identified seven temporal major clusters of interest on the topic COVID-19: 1) Chinese, 2) Italian, 3) Waiting, 4) Mitigations, 5) Social distancing and Lockdown, 6) Anti-crisis shield, 7) Restrictions releasing. There was an exponential increase of interest when the Polish government “declared war against disease” around 11/12.03.20 with a massive mitigation program. Later on, there was a decay in interest with additional phases related to social distancing and an anti-crisis legislation act with local peaks. We have found that declarations of mitigation strategies by the Polish prime minister or the minister of health gathered the highest attention of Internet users. So enacted or in force events do not affect interest to such extent. Traditional news agencies were ahead of social media (mainly Twitter) in dissemination of information. We have observed very weak or even negative correlations between a colloquial searching term 'antiviral mask' in Google, encyclopaedic definition in Wikipedia “SARS-CoV-2” as well official incidence series, implying different mechanisms governing the search for knowledge, panic related behaviour and actual risk of acquiring infection. Conclusions: Traditional and social media do not only reflect reality, but also create it. Risk perception in Poland is unrelated to actual physical risk of acquiring COVID-19. As traditional media are ahead of social media in time, we advise to choose traditional news media for a quick dissemination of information, however for a greater impact, social media should be used. Otherwise public information campaigns might have less impact on society than expected.

Social Values Are Significant Factors in Control of COVID-19 Pandemic – Preliminary Results (preprint)

Registry and survey data gave an opportunity to compare possible roles of social attitudes and social values in control and limit the COVID-19 pandemic. We analysed social values and time series of daily R0 (reproduction rate) estimates for 27 European countries. Embedded and affective autonomy are significantly negatively associated (p-Value<0.05) with controlled R0. It could mean that well interconnected societies with high attention to maximize utilities are more likely to couple with COVID-19. Hierarchy is significantly positively associated (p-Value<0.05) with controlled R0. Thus, hierarchical structures could inhibits control of COVID-19. The results emphasize the need to pay more attention to social values context in evaluating the effectiveness of mitigation strategies internationally.

TRENDS IN PERCEPTION OF COVID-19 IN POLISH INTERNET (preprint)

INTRODUCTION: Due to the spread of SARS CoV-2 virus responsible for COVID-19 disease, there is an urgent need to analyse COVID-2019 epidemic perception in Poland. This would enable authorities for preparation of specific actions minimizing public health and economic risks. This study aims to illustrate the media exposure of the social perception of coronavirus using the means available during the epidemic and our goal is to signal the main issues in public perception and medical commutation in real time.METHODS: We study the perception of COVID-2019 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet (on mainly Google and supported by Twitter, YouTube, Wikipedia and electronic media represented by Event Registry) from January 2020 to 07.04.2020 (before and after official introduction to Poland on 04.03.2020). To this end we utilize trend analysis with a support of simple natural language processing techniques. Each examined internet platform was analysed representativeness and composition of the target group too.RESULTS: We identified three temporal major clusters of interest before disease introduction on the topic COVID-2019: China- and Italy-related peaks on all platforms, as well as a peak on social media related to the recent special law on combating COVID-2019. Besides, there was a peak in interest on the day of officially confirmed introduction as well as an exponential increase of interest when the Polish government “declared war against disease” around 11/12.03.2020 with a massive mitigation program. Later on, there is a decay in interest with additional phases: social distancing and anticrisis act with local peaks. From a sociolinguistic perspective, we found that concepts and issues of threat, fear and prevention prevailed before introduction. After introduction, practical concepts about disease and epidemic dominate. We have found out that declarations of mitigation strategies by Polish Prime Minister or Minister of Health gather high attention on Internet users. So enacted or in force events do not affect interest in such an extent. We have observed very low correlation between colloquial searching term 'antiviral mask' in Wikipedia and encyclopaedic definition at Wikipedia “SARS-CoV-2”, which suggest that there are different mechanisms for searching for knowledge against panic related behaviour. CONCLUSIONS: Traditional and social media do not only reflect reality, but also create it. As traditional media ahead social media in time, we advise to choose news for a quick dissemination of information, however for a greater impact, social media should be used. Otherwise public information campaigns might have less impact on society than expected. For greater penetration, it might be necessary to diversify information channels to reach as many people as possible.

Attempt to Understand Public Health Relevant Social Dimensions of COVID-19 Outbreak in Poland (preprint)

Recently, the whole of Europe, including Poland, have been significantly affected by COVID-19 and its social and economic consequences which are already causing dozens of billions of euros monthly losses in Poland alone. Social behaviour has a fundamental impact on the dynamics of spread of infectious diseases such as SARS-CoV-2, challenging the existing health infrastructure and social organization. Modelling and understanding mechanisms of social behaviour (e.g. panic and social distancing) and its contextualization with regard to Poland can contribute to better response to the outbreak on a national and local level.In the presented study we aim to investigate the impact of the COVID-19 on society by: (i) measuring the relevant activity in internet news and social media; (ii) analysing attitudes and demographic patterns in Poland. In the end, we are going to implement computational social science and digital epidemiology research approach to provide urgently needed information on social dynamics during the outbreak.This study is an ad hoc reaction only and our goal is to signal the main areas of possible research to be done in future and cover issues with direct or indirect relation to public health.

Attempt to understand public health relevant social dimensions of COVID-19 outbreak in Poland (preprint)

Recently, the whole of Europe, including Poland, have been significantly affected by COVID-19 and its social and economic consequences which are already causing dozens of billions of euros monthly losses in Poland alone. Social behaviour has a fundamental impact on the dynamics of spread of infectious diseases such as SARS-CoV-2, challenging the existing health infrastructure and social organization. Modelling and understanding mechanisms of social behaviour (e.g. panic and social distancing) and its contextualization with regard to Poland can contribute to better response to the outbreak on a national and local level.In the presented study we aim to investigate the impact of the COVID-19 on society by: (i) measuring the relevant activity in internet news and social media; (ii) analysing attitudes and demographic patterns in Poland. In the end, we are going to implement computational social science and digital epidemiology research approach to provide urgently needed information on social dynamics during the outbreak.This study is an ad hoc reaction only and our goal is to signal the main areas of possible research to be done in future and cover issues with direct or indirect relation to public health.

Perception of emergent epidemic of COVID-2019 / SARS CoV-2 on the Polish Internet (preprint)

Problem: Due to the spread of SARS CoV-2 virus infection and COVID-2019 disease, there is an urgent need to analyze COVID-2019 epidemic perception in Poland. This would enable authorities for preparation of specific actions minimizing public health and economic risks. Methods: We study the perception of COVID-2019 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet (on Twitter, Google, YouTube, Wikipedia and electronic media represented by Event Registry) from January 2020 to 12.03.2020 (before and after official introduction to Poland on 04.03.2020). To this end we utilize data mining, social network analysis, natural language processing techniques. Each examined internet platform was analyzed for representativeness and composition of the target group. Results: We identified three major cluster of the interest before disease introduction on the topic COVID-2019: China- and Italy-related peaks on all platforms, as well as a peak on social media related to the recent special law on combating COVID-2019. Besides, there was a peak in interest on the day of officially confirmed introduction as well as an exponential increase of interest when the Polish government declared war against disease with a massive mitigation program. From sociolingistic perspective, we found that concepts and issues of threat, fear and prevention prevailed before introduction. After introduction, practical concepts about disease and epidemic dominate. Twitter reflected the clear, structural division of the Polish political sphere. We were able to identify potential sources of misinformation as well as key actors (especially early adopters) and influencers. Conclusions: Traditional and social media not only reflect reality, but also create it. Polish authorities, having a reliable analysis of the perception of the problem, could optimally prepare and manage the social dimension of the current epidemic and future ones. Due to filter bubbles observed on Twitter, public information campaigns might have less impact on society than expected. For greater penetration, it might be necessary to diversify information channels to reach as many people as possible which might already be happening. Moreover, it might be necessary to prevent the spread of disinformation, which is now possible due to the special law on combating COVID-2019.