Reduce Death Rates Research Articles

Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model.

ObjectiveThe provision of healthcare facilities remains high on the manifesto of various political parties in Pakistan and healthcare spending has witnessed a significant surge in the last two decades that is expected to positively influence health outcomes in the country. Therefore, this research aims to explore the effects of healthcare expenditures on the actual health status of the masses in Pakistan for the period 1995Q1 to 2017Q1.MethodsWe apply the Quantile Autoregressive Distributed Lag (QARDL) approach for estimation purposes. This is the most recent and emerging estimation technique in time series analysis.ResultsOur findings confirm that public healthcare spending significantly impacts health outcomes in Pakistan both in the short-run and long-run. Public healthcare spending improves life expectancy and reduces death rate and infant mortality.ConclusionThe study concludes that public healthcare is the main focus of the current regime. It is noticed that spending on healthcare significantly contributes to the health outcomes in Pakistan. These efforts by the government significantly promote life expectancy and drop down the mortality ratio in the country. Based on these notable facts, the government should allocate sufficient resources towards the latest healthcare technologies and equipment to optimize health outcomes in the country.

The Efficacy of Government Strategies to Control COVID-19: Evidence from 22 High COVID Fatality Rated Countries

This study aims to explore the efficacy of government policy directions in mitigating the effects of the COVID19 pandemic by employing a panel of 22 high Covid fatality rated countries throughout the 2020-first quarter of 2021. The panel ARDL model is employed to examine this phenomenon and to investigate the long-run effects of government policy decisions on infection and mortality rates from the pandemic. The study reveals that: (i) income support and debt relief facilities and stringent standards of governments reduce both infection and death rates; (ii) a timely response from governments has a positive effect on reducing death rates and a negative effect on infection rates; (iii) financial investments in confinement and health care are positively related to infection rates and negatively related to mortality rates. This study concludes by suggesting the importance of implementing precise policy decisions to lower infections and reduce deaths.Funding: There were no sources of funding used to prepare this study.Declaration of Interests: The authors have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject focus or materials discussed in this study.

Pneumocytes are distinguished by highly elevated expression of the ER stress biomarker GRP78, a co-receptor for SARS-CoV-2, in COVID-19 autopsies.

Vaccinations are widely credited with reducing death rates from COVID-19, but the underlying host-viral mechanisms/interactions for morbidity and mortality of SARS-CoV-2 infection remain poorly understood. Acute respiratory distress syndrome (ARDS) describes the severe lung injury, which is pathologically associated with alveolar damage, inflammation, non-cardiogenic edema, and hyaline membrane formation. Because proteostatic pathways play central roles in cellular protection, immune modulation, protein degradation, and tissue repair, we examined the pathological features for the unfolded protein response (UPR) using the surrogate biomarker glucose-regulated protein 78 (GRP78) and co-receptor for SARS-CoV-2. At autopsy, immunostaining of COVID-19 lungs showed highly elevated expression of GRP78 in both pneumocytes and macrophages compared with that of non-COVID control lungs. GRP78 expression was detected in both SARS-CoV-2-infected and un-infected pneumocytes as determined by multiplexed immunostaining for nucleocapsid protein. In macrophages, immunohistochemical staining for GRP78 from deceased COVID-19 patients was increased but overlapped with GRP78 expression taken from surgical resections of non-COVID-19 controls. In contrast, the robust in situ GRP78 immunostaining of pneumocytes from COVID-19 autopsies exhibited no overlap and was independent of age, race/ethnicity, and gender compared with that from non-COVID-19 controls. Our findings bring new insights for stress-response pathways involving the proteostatic network implicated for host resilience and suggest that targeting of GRP78 expression with existing therapeutics might afford an alternative therapeutic strategy to modulate host-viral interactions during SARS-CoV-2 infections.

Pillbox: Medicine Recognition System for Chronic Patients using Raspberry Pi

Chronic disease has become important threat to be handled in today’s date. As per WHO the millions of people suffering from this disease and most of them are older ones. Overall death rate in country is effecting due to chronic disease. The main reason of increased number of chronic patients is nothing but having lot of medications because of having number of health conditions as well as increased percentage of drugs in patient’s body. So, the system introduced successfully works to reduce death rate as well as to minimize drug intake in patient’s body. The system comprises of raspberry pi based pill recognition device namely “Pillbox”, Apache cloud based platform and android based mobile application.

Estimation output of Aceh cattle in livestock breeding and forage center of Indrapuri

Livestock Breeding and Forage Center (BPTU-HPT) Indrapuri is a technical implementation unit tasked with carrying out cattle breeding, especially the Aceh cattle. The objective of this study is to determine the estimated Aceh cattle output in BPTU-HPT Indrapuri, Aceh. Recording data covering the structure of the population, death and birth of cattle, expenditure, and income data in 2019 were used in this study. The results indicated that value of natural increase (NI) was 19.08%. Male cattle population exceeded 140.08% of the male breeding stock. Similary, the female population also was over the population’s female breeding stock (73.03%) with male and female net replacement rate (NRR) of 240.08% and 173.33%, respectively. Output estimation of Aceh cattle was 19.08% of population number. The calling rate of female cattle (5.58%) was almost twice compare to male Aceh cattle (3.92%). Meanwhile, male replacement stock remains at 5.49%, and female replacement remains at 4.09% of the total Aceh cattle population. In conclusion, Livestock Breeding and Forage Center (BPTU-HPT) Indrapuri is suitable as a source of Aceh cattle breeds, albeit it needs to be increased by natural increase through increasing birth rate and reducing death rate with better management so that it can be sustainable.

Cardiovascular effects of sodium‐glucose co‐transporter‐2 inhibitors and glucagon‐like peptide‐1 receptor agonists: The P value and beyond

Despite growing awareness of the dangers of a dichotomous interpretation of trial results based on the 'statistical significance' of a treatment effect, the uptake of new approaches has been slow in diabetes medicine. We showcase a number of ways to interpret the evidence for a treatment effect applied to the cardiovascular outcome trials of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose co-transporter-2 inhibitors (SGLT-2is): the P value function (or confidence curves), which depicts the treatment effect across the whole spectrum of confidence levels; the counternull value, which is the hazard ratio (i.e. treatment effect size) supported by the same amount of evidence as the null value (i.e. no treatment effect); and the S value, which quantifies the strength of the evidence against the null hypothesis in terms of the number of coin tosses yielding the same side. We show how this approach identifies potential treatment effects, highlights similarities among trials straddling the threshold of statistical significance, and quantifies differences in the strength of the evidence from trials reporting statistically significant results. For example, while REWIND, CANVAS and CREDENCE failed to reach statistical significance at the .05 level for all-cause mortality, their counternull values indicate that reduced death rates by 19%, 24% and 31%, respectively, are supported by the same amount of evidence as that indicating no treatment effect. Moreover, similarities among results emerge in trials of GLP-1RAs (REWIND, EXSCEL and LEADER) lying closely around the threshold of 'statistical significance'. Lastly, several S values, such as for the primary outcome in HARMONY Outcomes (S value 10.9) and all-cause death in EMPAREG-OUTCOME (S value 15.0), stand out compared with values for other outcomes and other trials, suggesting much larger differences in the evidence between these studies and several others that cluster around the .05 significance threshold. P value functions, counternull values and S values should complement the standard reporting of the treatment effect to help interpret clinical trials and make decisions among competing glucose-lowering medications.

Histo-CADx: duo cascaded fusion stages for breast cancer diagnosis from histopathological images.

Breast cancer (BC) is one of the most common types of cancer that affects females worldwide. It may lead to irreversible complications and even death due to late diagnosis and treatment. The pathological analysis is considered the gold standard for BC detection, but it is a challenging task. Automatic diagnosis of BC could reduce death rates, by creating a computer aided diagnosis (CADx) system capable of accurately identifying BC at an early stage and decreasing the time consumed by pathologists during examinations. This paper proposes a novel CADx system named Histo-CADx for the automatic diagnosis of BC. Most related studies were based on individual deep learning methods. Also, studies did not examine the influence of fusing features from multiple CNNs and handcrafted features. In addition, related studies did not investigate the best combination of fused features that influence the performance of the CADx. Therefore, Histo-CADx is based on two stages of fusion. The first fusion stage involves the investigation of the impact of fusing several deep learning (DL) techniques with handcrafted feature extraction methods using the auto-encoder DL method. This stage also examines and searches for a suitable set of fused features that could improve the performance of Histo-CADx. The second fusion stage constructs a multiple classifier system (MCS) for fusing outputs from three classifiers, to further improve the accuracy of the proposed Histo-CADx. The performance of Histo-CADx is evaluated using two public datasets; specifically, the BreakHis and the ICIAR 2018 datasets. The results from the analysis of both datasets verified that the two fusion stages of Histo-CADx successfully improved the accuracy of the CADx compared to CADx constructed with individual features. Furthermore, using the auto-encoder for the fusion process has reduced the computation cost of the system. Moreover, the results after the two fusion stages confirmed that Histo-CADx is reliable and has the capacity of classifying BC more accurately compared to other latest studies. Consequently, it can be used by pathologists to help them in the accurate diagnosis of BC. In addition, it can decrease the time and effort needed by medical experts during the examination.

Development of two-wheeler towed emergency purpose trailer for rescue operation

Ambulances are designed for quick response of emergency cases and to take a level of care for patients. Ambulances types are classified into four types based on their facilities. They are type A, type B, type C, type D. Type A is first responder. Type B is patient transport vehicle. Type C is basic life support ambulance. Type D is advanced life support ambulance. This work falls under category of type B. Type B ambulance is used to carry patient. Current work plan is to implement some main medical kit which is similar to type C ambulance. The project purpose is to focus on rural people to connect nearest health centre in the town area during emergency cases. Construction of trailed ambulance design is based on to overcome the problem faced by four wheeled ambulances in rural area. Also, the concept is based on to reduce death rate in village area and comfort ride in traffic places. Manufacturing cost of the ambulance is drastically reduced and also it could carry a patient and main necessary medical kit. Full body covered with sheet metal and patient compartment trailer unit is coupled with bike chassis frame during emergency cases. Trailer clamp is designed with adjustable length and width. Bike is uncoupled with trailer compartment and free to use when there is no emergency case.

Disaster risk governance for district-level landslide risk management in Bangladesh

The Government of Bangladesh has been successful in reducing death rates from tropical cyclones. However, in recent years, landslides have been a significant hazard, especially in the south-eastern part of Bangladesh. For example, the landslides of 2017 killed 110 people in Rangamati district. These deaths have raised an important question: whether district disaster risk governance at the local level is effective enough to mitigate the impact of landslide disasters? Based on literature review, nine good characteristics of disaster risk governance were selected (accountability, participation, collaboration, transparency, information sharing, shared decision making, communication, leadership and shared resources) to assess the effectiveness of district disaster risk governance for landslides underpinned by the disaster risk management cycle. These characteristics were assessed by interviewing 18 members of the Rangamati's District Disaster Management Committee. Policy documents were also reviewed to study the devolution of disaster risk governance urged by the Hyogo Framework and Sendai Framework for Disaster Risk Reduction. The findings suggest that the four principles (viz. accountability, participation, collaboration, and leadership) function satisfactorily during the response, evacuation, rescue and relief phases compared to the other five principles. The findings also suggest that the national Disaster Management Regulatory Framework and the Disaster Management Institutions are conducive to promote local disaster risk governance. However, there are challenges with regard to collaboration within and between state and non-state actors. As such, context specific recommendations are provided to improve collaboration and effectiveness with implications for other disaster-prone districts in Bangladesh.

Editorial: Coronavirus disease 2019 (COVID-19) - advances in epidemiology, diagnostics, treatments, host-directed therapies, pathogenesis, vaccines, and ongoing challenges.

Editorial: Coronavirus disease 2019 (COVID-19) - advances in epidemiology, diagnostics, treatments, host-directed therapies, pathogenesis, vaccines, and ongoing challenges.

Rapid Accurate and Accurate Medical Services System Innovation in Bangka Regency Depati Bahrin Hospital

Depati Bahrin Hospital experiencing an death rate increased from year to year, seen in 2015 the death rate in Dapati Bahrin Hospital have 348 people, while in 2016 amounted to 384 inhabitants. This is the background that there is a need for investment to reduce the death rate . This innovation makes the application of a fast service system medical accurate and precise. The method used is descriptive research with qualitative analysis application is proven to be effective to reduce death rate, in 2017 the death rate in Depati Bahrin hospital down to 308 people. It is hoped that in the future this application can be more developed and useful for mankind.

Survey on Machine Learning and Deep Learning Applications in Breast Cancer Diagnosis

Cancer is a fatal disease caused due to the undesirable spread of cells. Breast carcinoma is the most invasive tumors and is the main reason for cancer deaths in females. Therefore, early diagnosis and prognosis have become necessary to increase survivability and reduce death rates in the long run. New artificial intelligence technologies are assisting radiologists in medical image scrutiny, thereby improving cancer patients’ status. This survey enrolls peer-reviewed, newly developed computer-aided diagnosis (CAD) systems implementing machine learning (ML) and deep learning (DL) techniques for diagnosing breast carcinoma, compares them with previously established methods, and provides technical details with the pros and cons for each model. We also discuss some open issues, research gaps, and future research directions for the advanced CAD models in medical image analysis. Over the past decade, machine learning and deep learning have emerged as a subfield of artificial intelligence (AI), whose healthcare industry applications have provided excellent results with reduced cost and improved efficiency. This survey analyzes different classifiers of machine learning and deep learning approaches for breast cancer diagnosis. Results from previous studies proved that deep learning outperforms conventional machine learning for diagnosing breast carcinoma when the dataset is broad. Research gaps from the recent studies depict that practical and scientific research is an urgent necessity for improving healthcare in the long run.

TO STUDY THE EFFICACY OF AYURVEDIC TREATMENT IN COVID-19/SARS-COV-2

To overcome COVID-19 infection there is no any precise & effective management plan so far available in contemporary Medicine. Therefore, an attempt of administering Ayurvedic medicines to alleviate signs & symptoms of Novel Corona virus is taken into consideration. A clinical trial was performed in hospital with the combination of pure herbo-mineral Ayurvedic medicines named as ‘Shwashara’ along with modern medicines over 93 infected indoor subjects. In total sample size, 76.34% subjects had co-morbidities, after treatment it is been observed that, 29.58% of these subjects did not need oxygen support. 52.69% of sub-jects had HRCT score more than half. 58.06% were recovered within 7 Days. Out of 471 patients, who re-ceived only modern medicines had death rate of 10.02% and the Subjects treated with both systems of medicines have recorded 2.15% death. The ‘Shwashara’ medicine decreases symptoms of pneumonia & COVID-19, strengthen lungs and reduces death rate significantly.

Assessment of the timeliness and robustness for predicting adult sepsis

SummarySepsis is a leading cause of death among inpatients at hospitals. However, with early detection, death rate can drop substantially. In this study, we present the top-performing algorithm for Sepsis II prediction in the DII National Data Science Challenge using the Cerner Health Facts data involving more than 100,000 adult patients. This large sample size allowed us to dissect the predictability by age-groups, race, genders, and care settings and up to 192 hr of sepsis onset. This large data collection also allowed us to conclude that the last six biometric records on average are informative to the prediction of sepsis. We identified biomarkers that are common across the treatment time and novel biomarkers that are uniquely presented for early prediction. The algorithms showed meaningful signals days ahead of sepsis onset, supporting the potential of reducing death rate by focusing on high-risk populations identified from heterogeneous data integration.

Retrospective Review of Traditional Chinese Medicine Treatment of COVID-19 in China: Clinical Practice and Researches

In the fight against COVID-19 in China, traditional Chinese medicine (TCM) has played an important role in relieving symptoms, preventing deterioration, improving cure rate, reducing death rate, and promoting recovery. Since the third edition of the Diagnosis and Treatment Protocol for COVID-19 (simply referred to as the National Protocol), TCM has been included in the national guidance to tackle the epidemic. In order to make the international medical community fully understand the experience of TCM in the prevention and treatment of COVID-19, we comprehensively reviewed the history, etiology and pathogenesis, prevention and treatment, rehabilitation, and clinical and pharmacological research of TCM used in the endemic. The COVID-19 is under the category of plague or pestilence in TCM. Herbal medicine treatment for COVID-19 is mainly performed based on the syndrome differentiation of three stages and four types. The method also applies to acupuncture and moxibustion treatments. Herbal medicine granules and injections are used flexibly, and Western medicine is adopted to rescue patients in critical conditions. In rehabilitation, the integration of Chinese and Western medicine can be used to improve the respiratory and somatic function of patients. The role TCM has been playing in fighting this epidemic is a further proof of the effect of TCM in preventing and treating infectious diseases, and the relevant experience has been summarized and sublimated.

Mathematical modeling of COVID-19 infection dynamics in Ghana: Impact evaluation of integrated government and individual level interventions.

The raging COVID-19 pandemic is arguably the most important threat to global health presently. Although there Although there is currently a a a vaccine, preventive measures have been proposed to reduce the spread of infection but the efficacy of these interventions, and their likely impact on the number of COVID-19 infections is unknown. In this study, we proposed the SEIQHRS model (susceptible-exposed-infectious-quarantine-hospitalized-recovered-susceptible) model that predicts the trajectory of the epidemic to help plan an effective control strategy for COVID-19 in Ghana. We provided a short-term forecast of the early phase of the epidemic trajectory in Ghana using the generalized growth model. We estimated the effective basic Reproductive number Re in real-time using three different estimation procedures and simulated worse case epidemic scenarios and the impact of integrated individual and government interventions on the epidemic in the long term using compartmental models. The maximum likelihood estimates of Re and the corresponding 95% confidence interval was 2.04 [95% CI: 1.82–2.27; 12th March-7th April 2020]. The Re estimate using the exponential growth method was 2.11 [95% CI: 2.00–2.24] within the same period. The Re estimate using time-dependent (TD) method showed a gradual decline of the Effective Reproductive Number since March 12, 2020 when the first 2 index cases were recorded but the rate of transmission remains high (TD: Re = 2.52; 95% CI: [1.87–3.49]). The current estimate of Re based on the TD method is 1.74 [95% CI: 1.41–2.10; (13th May 2020)] but with comprehensive integrated government and individual level interventions, the Re could reduce to 0.5 which is an indication of the epidemic dying out in the general population. Our results showed that enhanced government and individual-level interventions and the intensity of media coverage could have a substantial effect on suppressing transmission of new COVID-19 cases and reduced death rates in Ghana until such a time that a potent vaccine or drug is discovered.

Pandemics and Aggregate Demand: A Framework for Policy Analysis

This paper studies the interaction between epidemiological dynamics and the dynamics of economic activity in a simple model in the structuralist/post-Keynesian tradition. On the one hand, rising economic activity increases the contact rate and therefore the probability of exposure to a virus. On the other hand, rising infection lowers economic activity through both supply and demand channels. The resulting framework is well-suited for policy analysis through numerical exercises. We show that, first, laissez-faire gives rise to sharp fluctuations in activity and infections before herd immunity is achieved. Second, absent any restrictions on economic activity, physical distancing measures have rather limited mitigating effects. Third, lockdowns are effective, especially at reducing death rates while buying time before a vaccine is widely rolled out, at the cost of a slightly more pronounced downturn in economic activity compared with alternative policies. This casts some doubt on the so-called “lives versus livelihood” policy trade-off. However, we also highlight the importance of policies aimed at mitigating the effects of the epidemic on workers’ income.

Lymphocyte subsets as a predictor of severity and prognosis in COVID-19 patients.

BackgroundCoronavirus disease 2019 (COVID-19) had become a worldwide health threat. Early prediction of the severity of COVID-19 patients was important for reducing death rate and controlling this disease.Methods and materialsA total of 301 patients confirmed with COVID-19 in Wuhan from 8 February to 10 April 2020 were included. Clinical data were collected and analyzed. Diagnostic and prognostic utility of blood cell counts and lymphocyte subsets in COVID-19 patients were investigated. The receiver operator characteristic curve (ROC) was used in discriminating the mild and severe/critical cases.ResultsThere were difference in blood cell counts and lymphocyte subsets among mild, severe and critical patients, which were also influenced by comorbidities and duration of disease. The area under the ROC of lymphocyte, CD3+ T cells, CD4+ T cells, and CD8+ T cells were 0.718, 0.721, 0.718, and 0.670, which were higher than that of other hematological parameters. The optimal threshold was 1205, 691, 402, and 177 per μl, respectively. Patients with higher counts of lymphocyte, CD3+ T cells, CD4+ T cells, or CD8+ T cells were correlated with shorter length of stay in hospital (p < 0.05). Multivariable Cox regression analysis showed disease severity, CD3+ T cells counts and time when the nucleic acid turned negative were independent risk factors for in-hospital death of COVID-19 patients (p < 0.05).ConclusionBlood cell counts and lymphocyte subsets correlated with severity of COVID-19.

Antimicrobial Activity of Biopolymer Extract against Four Selected Microorganisms

The discovery of antibacterial drugs to combat the spread of infectious diseases brought a great relief to the health community which allowed the medical professionals to treat and reduce death rate arising from infections caused by microorganisms. The need to search and formulate more potent and efficient antimicrobial drugs become necessary due to resistance of some microorganisms to available and existing antimicrobial drugs. Chitosan was extracted from crab shell waste through the stages of demineralization, deproteinization, and deacetylation. The chitosan (CHS) was further modified with silver nitrate (AgNO₃) solution using various concentrations (0.5, 1.0, and 1.5 M) in order to enhance its antimicrobial property. The crab shell powder (CSP) and chitosan (CHS) were characterized using X-ray diffraction (XRD), Fourier Transform Infrared (FT-IR), Scanning Electron Microscopy coupled with Energy Dispersive Spectroscopy. (SEM-EDS). The antimicrobial activity (zone of inhibition) was carried out using disk diffusion method. The result showed that <i>E.coli</i> and <i>Pseudopodium </i>showed the highest susceptibility of 10.2 ± 0.2 mm with extract from chitosan treated with 1.5 M silver nitrate (1.5 SNCHE) at 1000 µg/L whereas the least susceptibility was observed to be E. coli (2.0 ± 0.1 mm) with extract from chitosan treated with 1.0 M silver nitrate (1.0 SNCHE) at 250 µg/L. However, untreated chitosan extract (UCHSE) did not exhibit any antimicrobial effect against any of the tested microorganisms. The proximate analysis of CHS and CHN showed % crude protein to be 12.24 ± 0.01 and 20.54 ± 0.03 respectively. The FT-IR spectra of CHS and CHN showed their characteristic absorption peaks and the diffractograms of CSP and CHS revealed CaCO₃ to be the major mineral component in the samples.

Review Article on Convalescent Plasma Therapy For COVID-19

In December 2019, China witnessed a novel coronavirus (COVID 19) in Wuhan which eventually became a pandemic on March 11, 2020. No specific drugs, vaccines have been approved yet for its treatment as it is a novel virus, though convalescent plasma is expected to increase the survival rates and also it is easily available. Studies have shown that in every epidemic, medical professionals often use plasma because it is the only available option at that time. This passive antibody therapy has been used since the 1890s to treat emerging infections and diseases like measles, Ebola, H1N1 flu, polio, etc. Researchers at John Hopkins University were specially the first ones to get approval from the FDA for the clinical trials as in some cases of emergency, they tried plasma therapy and got success. After China and the US and several other countries showed relative improvement rates with convalescent plasma therapy, INDIA has therefore also given the go-ahead for framing a protocol to conduct a clinical trial for the same. Plasma collected from recovered COVID patients has neutralizing antibodies which are expected to reduce the duration of infection. According to the scientific data, Convalescent Plasma Therapy in COVID 19 seems effective, safe and reduces death rates. Further development of improved plasma, vaccines and other therapeutic agents depends on the quick generation of data on pathogenesis and immune response of SARS- COV-2