Effect of easing lockdown and restriction measures on COVID-19 epidemic projection: A case study of Saudi Arabia

Objectives- In this study we compared two predictions of COVID-19 cases in the Kingdom Saudi Arabia (KSA) using pre–and post–relaxation of lockdown period data to provide an insight regarding rational exit strategies. We also applied these projections to understand economic costs versus health benefit of lockdown measures. Methods- We analyzed open access data on COVID-19 cases from March 6 to January 16, 2021 in the KSA. To understand the epidemic projection during the pre- and post-lockdown period, we used two types of modeling: the SIR model, and the time series model. We also estimated the costs and benefits of lockdown- QALY gained compared to the costs of lockdown considering the payment threshold of the Government. Results- Prediction using lockdown period data suggested that the epidemic might slow down significantly after 109 thousand cases and end on October 6, 2020. However, analysis with latest data after easing lockdown measures suggested that epidemic might be close to an end on October 28, 2021 with 358 thousand cases. The peak has also been shifted from May 18, 2020 to Jun 24, 2020. While earlier model predicted a steady growth in mid-June, the revised model with latest data predicted it in mid-August. In addition, we estimated that 4986 lives would have been saved if lockdown continued but the cost per life saved would be more than $378 thousand, which is way above not only the KSA threshold, but also the threshold of any other highly advanced economies such as the UK and the USA. Conclusions- Our results suggest that relaxation of lockdown measures negatively impacts the epidemic. However, considering the negative impact of prolong lockdown measures on health and economy, countries must decide on the best timing and strategy to exit from such measures to safely return to normal life with minimum loss of lives and economy considering its economic and health systems’ capacity. Instead of focusing only on health, a balanced approach taking economy under consideration is recommended

Opportunities and obstacles to the elimination of malaria from Peninsular Malaysia: knowledge, attitudes and practices on malaria among aboriginal and rural communities

<p>Abstract</p> <p>Background</p> <p>Despite continuous efforts by the government and private sectors, malaria is still a public health problem in rural Peninsular Malaysia. This study investigated household knowledge, attitude and practices (KAP) regarding malaria in two malaria endemic communities, forest-aboriginal and rural communities, in the Lipis district of Pahang state, Malaysia.</p> <p>Methods</p> <p>A descriptive cross-sectional study with a semi-structured questionnaire was carried out among 100 and 123 households from forest-aboriginal and rural areas, respectively.</p> <p>Results</p> <p>Knowledge about malaria and its transmission is significantly higher among the rural participants than the aborigines (86.2% vs 76%, p < 0.01). However, use of medicinal plants and beliefs in witchcraft and sorcery in treating febrile diseases were significantly higher among the aboriginal population (p < 0.01). There were no significant differences between the two communities in terms of the knowledge about malaria symptoms, attitudes towards its severity and practices in preventive measures against malaria by using mosquito bed nets. However, the knowledge and practice of different preventive measures to combat malaria, such as insecticide and the elimination of breeding areas, was significantly higher among the rural population than the aborigines (p < 0.001).</p> <p>Conclusions</p> <p>Both communities were aware of malaria as a disease, but knowledge, attitudes and practices were inadequate. Providing efficient health education to people residing in malaria endemic areas would improve their understanding about malaria prevention in order to bring about the elimination of malaria from the country.</p

Content specificity of attentional bias to threat in post-traumatic stress disorder

Background: Attentional bias to affective information and reduced cognitive control may maintain the symptoms of post-traumatic stress disorder (PTSD) and impair cognitive functioning. However, the role of content specificity of affective stimuli (e.g., trauma-related, emotional trauma-unrelated) in the observed attentional bias and cognitive control is less clear, as this has not been tested simultaneously before. Therefore, we examined the content specificity of attentional bias to threat in PTSD

Fish farming in Tanzania: the availability and nutritive value of local feed ingredients

An investigative field survey was performed to gather baseline data on locally available feed ingredients and fish farming practices in different regions of Tanzania. More than 80% of respondents relied on locally available feed ingredients as a major feed supplement for their cultured fish, with maize bran being the most commonly used feed ingredient in all regions. Crude protein content in most analyzed local feed ingredients was medium-high, while crude fat content was high in some animal and agricultural by-products, and medium-low in other ingredients. Most respondents were males and the majority of fish farms were owned by individuals. Earthen pond was the most common fish farming system in all regions except Dar es Salaam. Semi-intensively mixed-sex tilapia monoculture was the dominating fish farming practice. The results of the survey presented provide a good platform for future development of culture systems and feeding strategies for tilapia in Tanzania

A Deep Learning Framework for the Detection of Abnormality in Cerebral Blood Flow Velocity Using Transcranial Doppler Ultrasound

Transcranial doppler (TCD) ultrasound is a non-invasive imaging technique that can be used for continuous monitoring of blood flow in the brain through the major cerebral arteries by calculating the cerebral blood flow velocity (CBFV). Since the brain requires a consistent supply of blood to function properly and meet its metabolic demand, a change in CBVF can be an indication of neurological diseases. Depending on the severity of the disease, the symptoms may appear immediately or may appear weeks later. For the early detection of neurological diseases, a classification model is proposed in this study, with the ability to distinguish healthy subjects from critically ill subjects. The TCD ultrasound database used in this study contains signals from the middle cerebral artery (MCA) of 6 healthy subjects and 12 subjects with known neurocritical diseases. The classification model works based on the maximal blood flow velocity waveforms extracted from the TCD ultrasound. Since the signal quality of the recorded TCD ultrasound is highly dependent on the operator's skillset, a noisy and corrupted signal can exist and can add biases to the classifier. Therefore, a deep learning classifier, trained on a curated and clean biomedical signal can reliably detect neurological diseases. For signal classification, this study proposes a Self-organized Operational Neural Network (Self-ONN)-based deep learning model Self-ResAttentioNet18, which achieves classification accuracy of 96.05% with precision, recall, f1 score, and specificity of 96.06%, 96.05%, 96.06%, and 96.09%, respectively. With an area under the ROC curve of 0.99, the model proves its feasibility to confidently classify middle cerebral artery (MCA) waveforms in near real-time.This work was made possible by the High Impact grant of Qatar University # QUHI-CENG-22_23-548 and student grant: QUST-1-CENG-2023-796. The statements made herein are solely the responsibility of the authors.Scopu

Specific, sensitive and rapid detection of human plasmodium knowlesi infection by loop-mediated isothermal amplification (LAMP) in blood samples

<p>Abstract</p> <p>Background</p> <p>The emergence of <it>Plasmodium knowlesi </it>in humans, which is in many cases misdiagnosed by microscopy as <it>Plasmodium malariae </it>due to the morphological similarity has contributed to the needs of detection and differentiation of malaria parasites. At present, nested PCR targeted on <it>Plasmodium </it>ssrRNA genes has been described as the most sensitive and specific method for Plasmodium detection. However, this method is costly and requires trained personnel for its implementation. Loop-mediated isothermal amplification (LAMP), a novel nucleic acid amplification method was developed for the clinical detection of <it>P. knowlesi</it>. The sensitivity and specificity of LAMP was evaluated in comparison to the results obtained via microscopic examination and nested PCR.</p> <p>Methods</p> <p>LAMP assay was developed based on <it>P. knowlesi </it>genetic material targeting the apical membrane antigen-1 (AMA-1) gene. The method uses six primers that recognize eight regions of the target DNA and it amplifies DNA within an hour under isothermal conditions (65°C) in a water-bath.</p> <p>Results</p> <p>LAMP is highly sensitive with the detection limit as low as ten copies for AMA-1. LAMP detected malaria parasites in all confirm cases (n = 13) of <it>P. knowlesi </it>infection (sensitivity, 100%) and none of the negative samples (specificity, 100%) within an hour. LAMP demonstrated higher sensitivity compared to nested PCR by successfully detecting a sample with very low parasitaemia (< 0.01%).</p> <p>Conclusion</p> <p>With continuous efforts in the optimization of this assay, LAMP may provide a simple and reliable test for detecting <it>P. knowlesi </it>malaria parasites in areas where malaria is prevalent.</p

Factors Associated with High Prevalence of Intestinal Protozoan Infections among Patients in Sana'a City, Yemen

Intestinal protozoan diseases in Yemen are a significant health problem with prevalence ranging from 18% to 27%. The present study is a cross-sectional study aimed at determining the factors associated with the high prevalence of intestinal protozoan infections among patients seeking health care in Sana'a City, the capital of Yemen. (0.4%). Multivariate analysis using forward stepwise logistic regression based on intestinal protozoan infections showed that contact with animals (OR = 1.748, 95% CI = 1.168–2.617) and taking bath less than twice a week (OR = 1.820, 95% CI = 1.192–2.779) were significant risk factors of protozoan infections. infections being most common. Statistical analysis indicated that low personal hygiene and contact with animals were important predictors for intestinal protozoan infections. As highlighted in this study, in order to effectively reduce these infections, a multi-sectoral effort is needed. Preventive measures should include good hygienic practices, good animal husbandry practices, heightened provision of educational health programs, health services in all governorates including rural areas. Furthermore, it is also essential to find radical solutions to the recent water crises in Yemen

iWorksafe: Towards Healthy Workplaces During COVID-19 With an Intelligent Phealth App for Industrial Settings

The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with resulting psychological and economic sequela. As countries start to ease lock-down measures and reopen industries, ensuring a healthy workplace for employees has become imperative. Thus, this paper presents a mobile app-based intelligent portable healthcare (pHealth) tool, called i WorkSafe, to assist industries in detecting possible suspects for COVID-19 infection among their employees who may need primary care. Developed mainly for low-end Android devices, the i WorkSafe app hosts a fuzzy neural network model that integrates data of employees’ health status from the industry’s database, proximity and contact tracing data from the mobile devices, and user-reported COVID-19 self-test data. Using the built-in Bluetooth low energy sensing technology and K Nearest Neighbor and K-means techniques, the app is capable of tracking users’ proximity and trace contact with other employees. Additionally, it uses a logistic regression model to calculate the COVID-19 self-test score and a Bayesian Decision Tree model for checking real-time health condition from an intelligent e-health platform for further clinical attention of the employees. Rolled out in an apparel factory on 12 employees as a test case, the pHealth tool generates an alert to maintain social distancing among employees inside the industry. In addition, the app helps employees to estimate risk with possible COVID-19 infection based on the collected data and found that the score is effective in estimating personal health condition of the app user

Prevalence of head lice and hygiene practices among women over twelve years of age in Sindh, Balochistan, and North West Frontier Province: National Health Survey of Pakistan, 1990-1994

Background: Head lice infestation is an infection of the scalp and skin which causes blood loss, discomfort, and social and psychological distress with the possibility of secondary bacterial infections occurring at scratch sites. In Pakistan, although some small scale studies have been conducted to investigate prevalence of head lice in school children and the general population, no population based estimates have been reported. The National Health Survey of Pakistan (NHSP 1990 - 94) was a nationally representative health examination survey of the Pakistani population. The NHSP is the first population based household survey to collect data on the prevalence of head lice in adult women in Pakistan. In this paper we use data from the NHSP to present an epidemiological profile of personal hygiene practices and head lice infestation among women aged 12 years or older in three provinces of Pakistan, Balochistan, Sindh and North West Frontier Province (NWFP). Results: Overall about 7% women aged 12 years and older suffered from head lice infestation. Multivariable logistic regression analysis identified factors independently associated with presence of head lice. Age less than 16 years and crowding at home were associated with higher infestation-rates. The impact of household socio-economic status on infestation rates among women was different in urban and rural settings, urban women with low socio-economic status were more vulnerable than similar women in rural settings. Bathing infrequently in summer was associated with higher prevalence rates only in Sindh, possibly due to the fact that among the three provinces Sindh has a hotter and more humid summer. Conclusions: The results of our analysis of NHSP indicate high levels of head lice infestation among girls and women in the three Provinces. The epidemiological profile of hygienic practices of women indicated that NWFP and Balochistan as compared to Sindh, and rural as compared to urban areas were less developed with respect to access to water supply and soap for maintaining personal hygiene. Simple and cost-effective measures such as provision of water and soap, and improving awareness regarding maintaining personal hygiene can contribute significantly towards improving public health status of the women in Pakistan

Measures, Gaps, and Mitigation Strategies in Bangladesh’s COVID-19 Response

AbstractThe Coronavirus Disease 2019 (COVID-19) spread rapidly from China to most other countries around the world in early 2020 killing millions of people. To prevent virus spread, world governments implemented a variety of response measures. This paper’s objectives were to discuss the country’s adopted measures to combat the virus through June 2020, identify gaps in the measures’ effectiveness, and offer possible mitigations to those gaps. The measures taken included screening device deployment across international air and land ports, flight suspensions and closures from COVID-19 affected countries, and declaration and extension of a national public holiday (equivalent to lockdowns in other countries). Identified gaps were test kit, PPE, ICU beds, and ventilator shortages, limited public awareness, and insufficient coordination and collaboration among national and international partners. Proper and timely risk mapping, preparedness, communication, coordination, and collaboration among governments and organizations, and public awareness and engagement would have provided sufficient COVID-19 mitigation in Bangladesh. </jats:p