Costs Associated with A COVID-19 Screening Test, Country Comparison Editorial

Introduction

The COVID-19 pandemic has created an unprecedented need for diagnostic testing. In early 2020, diagnostic manufacturers were still struggling to raise the capacity of the new COVID-19 test to a reasonable level, but due to limited supply and high demand, prices became a challenge to low- and medium-income countries [1]. COVID-19 screening tests are essential in tracking where countries are in terms of COVID-19 and how far they need to act to combat /and manage it. There are two types of tests currently being conducted, namely the COVID-19 Polymerase Chain Reaction (PCR) and Rapid Antigen Tests. The PCR tests whether a person has the virus, whereas the Rapid Antigen tests whether a person has developed antibodies against the virus, assuming they have previously contracted the virus and whether their immune system produced antibodies in response to the infection. In South Africa, a COVID-19 test is accessible in a public sector setting; however, in a private setting, the RT-PCR tests cost R850 and results are available within 24 hours. Rapid Antigen Tests cost R400 providing results within 15-30 minutes [2]. The CMS alleged that laboratory prices for COVID-19-tests were exorbitant and unjustifiable at R850 per test. As of 12th December 2021, the cost of the RT-PCR test had been revised to not more than R500. The reduction of 41% decline followed a complaint by the Council for Medical Schemes (CMS) to the Competition Commissioner that private laboratories were [3].
A COVID-19 test can be taken at a doctor’s room, in a laboratory with a medical prescription, a pharmacy, a screening centre, or even a hospital setting. The test is costly when it is carried out in private laboratories and the price varies per laboratory. The intervention by the CMS, which led to a price reduction, has been widely welcomed in the private sector. It has also been accepted as a victory for patients utilising private laboratories, especially those patients would require more frequent testing as the variants emerge ad mutate differently. Real-time- PCR is the most accurate diagnostic test for COVID-19, as it is more reliable than a rapid antigen test because of its high sensitivity and specificity to the virus. The PCR tests, which require a small saliva sample, have a sensitivity of 94% and specificity of 100%. In contrast, Antigen tests, which detect viral surface proteins, can provide a rapid and accurate indication of active infection, and provide a sensitivity of 97·1% and specificity of 98·5% [1,4]. Disparities in the price of a COVID-19 test vary by country, as shown in Table 1. COVID-19 as global pandemic has affected all countries across the globe, the recent new variant omicron has servery affected countries such as Europe a depicted in figure 1. Testing and tracing are one of the main strategies used to screen patients infected by the virus. A pandemic such as COVID-19 is financed mainly by governments through national budgets allocated to the ministries of health. Public sector testing is free of charge. However, should patients choose to test in a private setting or laboratory, there are costs associated. As of 11 December, the National Institute for Communicable Diseases (NICD) reported a total of 20 176 391 COVID-19 tests that have been conducted , with the private sector accounting for 54% of all tests conducted [5-14].

Figure 1: Daily new confirmed COVID-19 cases per million people [14].

Table 1: Comparison Analysis country’s PCR test prices.

Conclusion

This editorial showed varying costs associated with COVID-19 tests depending on the setting, geographic region, and country. High extremal values of COVID-19 tests costs in other countries indicate an urgent need to regulate prices associated with a COVID-19 test. The case study of CMS in South Africa is essential key learning for other countries on how stakeholders and consumers can intervene of fair practice, competition, product, and services relating to the pandemic can be scrutinised for fairness. This editorial further calls for transparency in all input’s costs associated with COVID-19 tests. This is to ensure that the private sector does not unduly benefit or employ profit driven approaches or practices during a pandemic such as COVID-19. Lastly, the review of costs associated with COVID-19 tests should be a function of an ever-changing environment coupled with increased demand for the product or service and the emergence of new variants which may well require patients more frequents testing.

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Mini-Review in Bone Marrow Aspirate Concentrate

Mini Review

A Bone Marrow Aspirate Concentrate procedure (BMAC) is an innovative regenerative method implemented in medical practice since the early nineteenth century as a simple medical relief that grew steadily through good experiences and training. Consequently, these undifferentiated stem cells create diverse kinds of differentiated cells. [1]. The BMAC procedure is an uncomplicated technique that runs on various diseases not cured by traditional remedies or pathologies that need principal medicine. Therefore, in the BMAC method, the operator inserted the BMAC in the hurt tissue to form subsequent physiological chains in the involved tissue. Consequently, the BMAC exhibited the capability to assist the diseased tissue microstructure for tissue reconstruction over time. [2]. The earlier BMAC testers attempted victorious trials of the BMAC method in animals and later in humans with excellent outcomes. Furthermore, the experimenters illuminated the growing pertinence of the BMAC in many disorders and unmanaged conditions [3]. BMAC method included catching a small amount of the participant bone marrow from the (anterior or posterior part of the pelvis) by local an aesthesia as an outpatient procedure. The operator transfers this part of bone marrow to a specialized laboratory in an aseptic way.
Hence, the laboratory operator collects the stem cells by an activation device like “Adi-Stem, AdiLight-2 Photo device” and guards these stem cells to reinsert them into the same patient blood or the diseased tissue for the cure [4]. Consequently, the doctor proffered the sufferer a painkiller and advised of bed rest for a week. After that, the specialist will follow the patients with education and rehabilitation after the BMAC shot, but if the patient did not benefit from the first shot of BMAC, the physician gave a second injection after three weeks [5]. BMAC accommodates immature stem cells plus growth factors, which gave more influence than the “autologous platelet-rich plasma”. Hence, this plasma holds the growth factors only. Afterward, this essential contrast offers the BMAC effectiveness in tissue regeneration plus emblematic symptom amelioration [6]. In 2020, the Food and Drug Administration (FDA) in the USA approved “blood-forming stem cells” or “hematopoietic progenitor cells” from umbilical cord blood, but in 2021 the USA approved other types of stem cells. Nevertheless, some principal academic hospitals in the USA and developed nations with excellent results. Further, Native Stem Cell Hospitals practiced BMAC treatment following 2014. Moreover, in 2020 the Food and Drug Administration acquired specific guidelines [7].

Uses of BMAC

A. Musculoskeletal Conditions

1. Accelerate Fracture Healing
2. Cure Non-United Fractures
3. Cure Early Osteoarthritis
4. Reliving Osteoarthritic Pain
5. Cure Early Osteonecrosis
6. Enhance Cartilage Repair and Capacity
7. Cure Osteochondritis
8. Delay Arthritic Progress
9. Cure Ligament Injuries
10. Cure Disc Disease
11. Heal Meniscal Injuries

B. Skin

1. Heals Chronic Skin Wounds
2. Treat Chronic Skin Ulcers
3. Treat Difficult Burns

C. Nerves

1. Cure Spinal Cord Injuries
2. Heals
3. Cerebral palsy

D. Wounds

1. Heal chronic wounds
2. Repairing muscle loss
3. Improve muscle healing

E. Diabetes

1. Cure type 1 diabetes mellitus
2. Lowering blood sugar in type 2 diabetes mellitus
3. Repair diabetic foot

F. Ischemia

1. Congestive Heart Failure
2. Heart Failure
3. Critical limb ischemia

G. Eye Diseases

1. Usher syndrome
2. Serpiginous Choroidopathy
3. Dominant Optic Atrophy

H. Ear Diseases

1. Usher syndrome
2. Ear Cartilage loss
3. Cochlear disease

I. Brain

1. Autism
2. Stroke
3. Traumatic Brain

Complications of BMAC

A. Most of those complexities are minor and settle spontaneously.
1. Pain in situ
2. Simple discomfort
3. Hematoma
4. Numbness
5. Need repeated applications

Limitations of BMAC Procedure

1. Not Licensed in Some Countries
2. Expensive
3. Not In Health Insurance List
4. Repeated Injections
5. Need Special Laboratory Tools

Results

BMAC procedure is harmless, comfortable, safe, plus high satisfaction technique. Furthermore, BMAC had lower patient mortality plus morbidity.

Conclusion

BMAC is a good choice in curing or alleviating man’s difficultto- treat diseases.

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Motor Relearning Program in Water: Surgery or Aqua-Therapy?

Opinion

The use of hydrotherapy for healing has been practiced for centuries by the ancient Iranians, Greeks, Chinese and ancient Romans due to the unique properties of water. The use of hot springs was common among the people of that time to relieve and reduce all kinds of pain [1]. Today, different terms such as hydrotherapy (hydrotherapy), aqua-therapy, pool therapy, water sports, etc. are mentioned in different communities. Three important properties of water that cause the main difference between exercise in water and land:
1- Floating force, which causes weight loss in water. This weight loss can occur up to 90% (water depth to the neck), for example, a person who weighs 100 kg can lose up to 10 kg in water, which is the weight loss that causes the joints to overlap Reduce the pressure on them and relieve and reduce pain.
2- Viscosity or adhesion of water, this property of water, causes water resistance against body movements and strengthens various muscles. On the other hand, the force of water adhesion helps maintain balance and reduces falls in the elderly. Various studies have shown that one of the most important reasons for the inactivity of the elderly on land is the fear of falling and bone fractures, which makes water safe for the elderly to exercise safely without any injuries or falls.
3- Hydrostatic pressure: It is the pressure that water puts on different organs of the body simultaneously and causes the return of blood from the lower extremities to the heart to increase, and this improves the function of the heart and lungs, so exercising in water Due to its light weight, weight loss and easy and fast return of blood to the heart can be beneficial for cardiopulmonary patients [2].
The skin of the body is an important and essential organ that is stimulated by the collision of the skin’s nerve receptors and has a positive effect on the central nervous system (brain and spinal cord) through the nerves, which ultimately calms the mind and reduces stress. Numerous studies have shown that the stress factor is one of the most important causes of cardiovascular disease, stroke and eventually death, so exercising in water is a very good tool to prevent these risks [3]. Also, exercise in water due to heat and water resistance can consume up to about twice as many calories in dry time and is very effective in weight loss. On the other hand, due to weight loss in water, damage to various joints, including the knees and back, is greatly reduced. Therefore, people who are overweight or obese are strongly advised to exercise in order to prevent knee wear and joint injuries [4]. Follow yourself in the water until you reach your ideal weight. In addition to the benefits mentioned above, various studies have shown the beneficial effects of water exercise in reducing harmful blood fats, regulating blood sugar in diabetics, modulating blood pressure in hypertensive people, reducing joint pain such as rheumatoid arthritis, improving neurological disorders. Parkinson’s and MS have been shown to reduce depressive symptoms and increase life expectancy [2].
Lumbar disc injury can be considered as an important complication of the 21st century. Many people in the lower to upper age range suffer from lumbar disc herniation due to various causes such as inactivity, obesity and overweight, unprincipled and intense exercise, poor nutrition, and various accidents. This complication is associated with severe and unbearable pain in the more severe stages. Unfortunately, today, surgery has become popular because in most cases, the results are not satisfactory, and with the examinations performed on these patients, it can be said that surgery is not the complete end of back pain. My advice after years of experience in hydrotherapy and working in specialized hydrotherapy centers and dealing with patients with lumbar disc disease before and after surgery is to refrain from surgery as long as they can still walk, and instead, consult your doctor for at least one to three months (three times a week) under hydrotherapy and rest. It should be noted that even after surgery, hydrotherapy courses should be used for postoperative rehabilitation, so it is better to do this before surgery. Due to the properties of water and its beneficial mechanisms for people mentioned above, hydrotherapy can be very effective and miraculously in reducing back pain caused by lumbar disc herniation [5]. Numerous feedbacks from such patients with me as well as research in this field are proof of this claim.
Therefore, surgery should be the last resort. Todays, use of other pool facilities such as sauna (dry and steam), Jacuzzi and cold water pool can also be considered as hydrotherapy supplements. The general public may consider the use of saunas as a means of weight loss, which is a misconception. When people use the sauna, especially dry ones, they lose a lot of body water, and when they drink water again, this water is replaced. The benefits of using saunas include its positive effects in increasing relaxation, reducing muscle spasms, opening skin pores, improving the airways and increasing blood flow. Jacuzzi and cold water pool also help relieve bruises and fatigue. Of course, the use of Jacuzzi, cold water and saunas should be observed in accordance with safety principles, and the elderly, patients with cardiovascular failure, people with respiratory problems and patients with neurological disorders should not use. It is also not advisable to use hydrotherapy in people with open wounds and infections until they have healed. People with cardiovascular failure and endocrine disorders should consult their doctor for hydrotherapy.

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Biostatistical Analysis on Anti-breast Cancer Drug Screening

Introduction

Breast cancer is one of the most common malignant tumors in women, and a malignant tumor occurring in ductal epithelium of the breast. Estrogen is involved in the growth and differentiation of mammary epithelial cells in hormone dependent tumors. It plays an important role in the occurrence and development of breast cancer [1]. Estrogen mainly acts through the estrogen receptor expressed in the nucleus, that is, by binding with estrogen receptor (ER) to form a complex [2]. Research shows that ERα is expressed in normal breast epithelial cells less than 10% but expressed in breast cancer cells around 50%-80%. ERα has become an important target of endocrine therapy for breast cancer [3]. Currently, antihormone therapy is commonly used in breast cancer patients with ERα expression, which controls estrogen levels through regulating estrogen receptor activity. ERα mediates the E2 up regulation of PI3K/Akt signaling pathway and promotes cell proliferation [4]. Compounds that can antagonize ERα activity may be candidates for treatment of breast cancer. For example, tamoxifen and renoxifene are the ERα antagonists for clinical treatment of breast cancer [5]. In order to screen potential active compounds, a potential compound model is usually established to collect compounds and bioactive data by targeting the specific estrogen receptor subtype targets associated with breast cancer. The quantitative structureactivity relationship (QSAR) model of compounds was constructed with the biological activity descriptor as the independent variable and the biological activity of compounds as the dependent variable. The model was used to predict the new compound molecules with good biological activity or guide the structural optimization of existing active compounds. A compound that wants to become a candidate drug, besides having good biological activity (here refers to anti breast cancer activity), also needs to have good pharmacokinetics and safety in human body. It is called ADMET property, including absorption, distribution, metabolism, excretion and toxicity. When determining the biological activity of a compound, it is also necessary to consider its ADMET properties as a comprehensive consideration. In this paper, the coupling degree between bioactivity descriptor and ER activity is verified by BP neural network. After determining that the screened bioactivity descriptors can indeed affect ERα activity to a great extent, the ADMET property of bioactivity descriptors is further verified.

Overview of BP Neural Network

Figure 1: Basic structure diagram of BP neural network.

Artificial neural network is widely used in pattern recognition, function approximation and so on. BP neural network is a multilayer feedforward network simulating human brain. It has good adaptability and training ability, belongs to nonlinear dynamic system, and including two processes: forward propagation of information and back propagation of error. BP neural network consists of three parts: input layer, hidden layer and output layer. The input layer receives the input information, and then transmits the information to the hidden layer. The hidden layer analyzes and processes the data. Finally outputs acceptable information through the output layer. This information is continuously corrected through the reverse propagation of error, which can make full use of the coupling between data. BP neural network shows excellent accuracy in many fields. Therefore, this paper selects neural network as the main prediction method. Whether it is regression network or prediction network, the setting of the hidden layer and the number of hidden nodes of the network is very important. Too few hidden layers and hidden nodes will lead to less data information that the neural network can process, resulting in low prediction accuracy, and too many hidden layers will lead to overfitting of the model. There is no general calculation formula for the setting of the optimal number of hidden nodes. It is more based on the empirical formula or changing the number of hidden nodes to continuously train the model to find the number of hidden nodes with the smallest error [6-8]. Basic structure diagram of BP neural network is shown in Figure 1. The activation function of BP neural network usually uses softmax function to give corresponding weight to each node and transfer information between nodes in the network. In addition, there is an offset weight in the propagation of each layer of network, which is an additional constant of SoftMax function. In the model training, the gradient optimization algorithm (Adam algorithm) is used to optimize the model to obtain the best results [9].

Its operating principle is shown in Figure 2.

Figure 2: Principle of Softmax function.

Adam Algorithm:
Initialize 1st, 2nd moment vector and timestep:

do while:

Computing the gradient:

Update biased first moment estimate:

Update biased second moment estimate:

Compute bias-corrected first moment estimate:

Compute bias-corrected second moment estimate:

Update parameters:

Where α is the step length, β ;β ε [0,1] is the momen estimation of exponential decay rate, and f(θ) is the random objective function of parameter θ. Adam algorithm will be used to optimize the parameters of BP neural network in order to accelerate convergence and improve accuracy. The model is:
• Step 1: Initialize the network weight and bias, give each network connection weight a small random number, and each neuron with a bias will also be initialized to a random number.
• Step 2: Forward propagation. Input a training sample, and then calculate the output of each neuron. The calculation method of each neuron is the same, which is obtained by the linear combination of its inputs.
• Step 3: The gradient descent method is used to calculate the error and carry out back propagation. The weight gradient of each layer is equal to the input of the connection of the previous layer multiplied by the weight of the layer and the reverse output of the connection of the next layer.
• Step 4: The weight gradient in the third step is used to adjust the network weight and neural network bias.
• Step 5: Back propagation, Adam algorithm is used to accelerate the weight adjustment, initialize the moment vector and exponential weighted infinite norm to 0, update the parameters through vector operation, and iterate in t time from step size to 1. Sort errors and return.
• Step 6: At the end of judgment, for each sample, judge if the error is less than the threshold set by us or has reached the number of iterations. We’ll finish training, otherwise, return step 2.

Data Description and Preprocessing

In this paper, the bioactivity description data set is used to verify the ERα activity and ADMET properties respectively. The description dataset contains 729 biological activity descriptors of 1974 compounds. Because the data dimension is too large and contains a large number of repetitions and useless variables, this paper selects 15 most representative biological activity descriptors from the 729 biological activity descriptors of 1974 compounds. Firstly, low variance filtering is used to delete the biological activity descriptors with low information, then considering the correlation and independence between variables, Lasso regression is used to select these variables, and finally considering the coupling degree between variables and ERα activity. The final 15 most representative biological activity descriptors are obtained. The specific steps are as follows:
• Step 1: Because the variance of variable can reflect the degree of dispersion, the variable with small variance contains little information, which cannot provide key and useful information for the construction of the model. Therefore, for 729 biological activity descriptors of 1974 compounds, the variance of 729 variables is calculated and arranged from large to small.
• Step 2: After cleaning the biological activity descriptors with low information or no information, use the remaining molecular descriptors to further process the repeated information of the data, so as to make the data relatively independent. In this paper, Lasso feature selection method is used to propose a variable from two variables with strong correlation to eliminate duplicate information. The essence of lasso feature selection method is to seek the sparse expression of the model and compress the coefficients of some features to 0, so as to achieve the purpose of feature selection. The parameter estimation of lasso feature selection method is as follows:

λ is a nonnegative regular parameter, which represents the complexity of the model. The greater its value, the greater the penalty of the linear model, λ Determined by cross validation.
• Step 3: Spearman rank correlation coefficient is a nonparametric index to measure the dependence of two variables, which can reflect the coupling degree between variables. This paper uses Spearman rank correlation coefficient to obtain the final 15 representative biological activity descriptors.
Three screening processes by Figure 3 shows, in step 1, 217 biological activity descriptors with variance greater than 1.3 were left. In step 2, 101 bioactivity descriptors were retained by lasso feature selection. In step 3, 101 biological activity descriptors are sorted according to Spearman rank correlation coefficient, leaving the most representative 15 biological activity descriptors. The final screening results are shown in Table 1. ADMET properties are composed of five aspects: absorption, distribution, metabolism, excretion and toxicity. The corresponding values are provided in the form of two classifications, ‘1’ represents good or yes, and ‘0’ represents poor or no. Comparison table of ADMET properties are shown in Table 2.

Figure 3: Principle of Softmax function.

Table 1: Comparison table of biological activity descriptor.

Table 2: Comparison table of ADMET properties.

Model Training and Prediction

In order to avoid over fitting and improve the generalization ability of the model [10], we cut the remaining 15 bioactivity descriptors into 80% of the training set and 20% of the test set. Considering the coupling and the nonlinear relationship between the data, the neural network is used for training and prediction, the training set is used to set the model parameters, and the test set is used to calculate the default accuracy and verify the rationality of the model. When training the model, we should also consider the convergence speed of the model. Neural network is a complex structure with large amount of calculation. When there are too many input variables in the input layer and the amount of data is too large, gradient optimization algorithm is usually used to accelerate the convergence speed of neural network. Adam algorithm is used for model optimization in this paper. The results are as follows:

Figure 4: The predict of Adam-BPNNet.

As can be seen from Figure 4, The red line is the logarithm of ERα, the blue line is the regression prediction result of neural network with one hidden layer, and the black line is the regression prediction result of neural network with two hidden layers. Among them, when the hidden layer is 1, the mean square error of prediction is 0.696, and when the hidden layer is 2, the mean square error of prediction is 0.759.Obviously, when the hidden layer is 1, the regression prediction result is more accurate, and the good prediction accuracy shows that the ERα activity can be controlled by controlling the 15 biological activity descriptors selected in this paper, so that we can inhibit the ERα activity. In order to ensure that the selected bioactivity descriptors have good medical properties, the ADMET properties of these 15 bioactivity descriptors were verified. The commonly used machine learning methods are used for multiple prediction to eliminate contingency. ROC curve shown in Figure 5. It can be seen from Table 3 that the three models show very high prediction accuracy, among which xgboost performs best. The three models show that CYP3A4 is highly coupled with 15 biological activity descriptors, HOB is the lowest coupled with one biological activity descriptor, but the prediction accuracy also reaches 0.895. This shows that the 15 biological activity descriptors selected in this paper can not only reflect ERα activity to a great extent, It can also reflect good ADMET properties.

Figure 5: ROC curve of each classification method.

Table 3: Comparison table of AUC values of different classification models.

Conclusion

The results show that the 15 biological activity descriptors selected in this paper can predict ERα activity with a low mean square error of 0.676, which indicates that there is a high coupling between them. In addition, they can also reflect the properties of ADMET at an average level of 0.948, so they have good medical value. The development of anti-breast cancer drugs is a complex and long process. In this process, it is necessary to test the effects of drugs containing various biological components on target cells. If all the combined drugs are tested, it will be a long process. In order to improve the development cycle and cost of anti-breast cancer drugs, we can consider using these bioactive descriptors to synthesize breast cancer resistant compounds. Because the experimental data are limited, the influence of these 15 bioactive descriptors on the activity of other target cells is not considered. Therefore, the bioactive descriptors selected in this paper have limitations in the effect of breast cancer. Furthermore, lasso feature selection method is used to screen bioactivity descriptors, which may omit some important bioactivity descriptors. When the synthetic breast cancer drugs are synthesized, the best value or range of bioactive descriptors can further reduce the development cost and development cycle of anti-breast cancer drugs. Therefore, in this paper, we can further study the best values of various bioactive descriptors. At the same time, we also hope that the variable screening method and validation method can be applied to more biopharmaceutical processes.

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Viet Nam’s Mandatory Motorcycle Helmet Law 2007 and its Impact on Road Traffic Injuries Mortality in a Mountainous Province: A Population-Based Mortality Registration, 2005-2018

Introduction

Road traffic injuries (RTIs) are a public health burden globally. The number of deaths due to road accidents worldwide is exceptionally high, with an estimated 1.35 million deaths and 20 - 50 million injuries each year (World Health Organization (WHO). 2020b). Road traffic is among the leading causes of mortalities due to injuries for all age groups, especially among children and youth and young adults aged 5 to 29 (World Health Organization (WHO). 2018). Globally, road injuries were responsible for more than 55 million years of life lost, 7 million years lived with disability, and 64 million disability-adjusted life years in total, with corresponding age-standardized rates of 745, 126, and 871 per 100,000 population, respectively James SL, et al. [1]. The two most common road traffic injuries are head and spinal cord injuries, which are the leading cause of death and trauma for motorcycle users (World Health Organization (WHO). 2018). Such injuries may result in an enormous economic burden and use extensive portions of a countries health expenditure (World Health Organization (WHO). 2013b, 2018). The risk of encountering RTIs among middle and low-income countries (LMICs) is three times higher than in higherincome countries (World Health Organization (WHO). 2020b).
Motorcycles are the most widely used transport in Viet Nam, accounting for more than 90% of total personal transport registrations (World Health Organization (WHO). 2013a). The average rate of annual road traffic injury mortality was reported approximately 18 per 100,000 population before 2007 (Health Environment Management Agency, Ministry of Health. 2011). In response to the rising burden due to RTIs, the Viet Nam government enacted a comprehensive helmet use legislation for motorcyclists in June 2007 (Government of the Socialist Republic of Viet Nam (GOV). 2007). This legislation included obligatory helmet-wearing rules to all two-wheeled and three-wheeled vehicles on all roads, with heavy fines for non-users, and increased enforcement Passmore, JW et al. [2]. The helmet use rate in Viet Nam immediately escalated from 40% in 2007 to over 95% in the following year and has remained steadily above 90% since then (World Health Organization (WHO). 2020a). The introduction of mandatory helmet-wearing legislation in Viet Nam was anticipated to have averted 2,200 deaths and 29,000 head injuries in the year 2008 Olson Z, et al. [3]. The helmetwearing law is useful, especially among less wealthy families.
Many countries have presented similar successful results of putting helmet-wearing laws into practice, resulting in head injuries dropping by 33% in Taiwan and 41% in Thailand after implementing such laws Chiu, WT, et al. [4,5]. Similar studies have examined the effectiveness of helmet law enactment on traffic mortality in Viet Nam. At the national level, traffic deaths related to motorcyclists, and total traffic deaths, in the year following the introduction of the helmet law in Viet Nam dropped by 36% and 18%, respectively Passmore, JW et al. [2,6]. The study by Phung et al. across all provinces in Viet Nam revealed that many areas experienced a significant decrease in potential years of life lost (PYLL) of more than 80% due to RTIs, and the summary post law PYLL stopped increasing six months of implementation helmet laws Phung D, et al. [7]. Another study in an outlying district of a large city in Viet Nam found that motorcycle-related injuries and deaths during the post-law period decreased significantly, by 47% and 31%, respectively Ha NT, et al. [8]. Although the efficacy of helmet laws was demonstrated in reducing road injuries and deaths at the national level, evidence in remote areas is still needed. This study aimed to evaluate the impact of mandatory helmet legislation on the potential change of mortality in Lang Son province, a large mountainous region in northern Viet Nam. This province has an area of 8.310,09 km2 with five national highways (Lang Son Provincial Statistics Office. 2019). Before 2007, the government implemented legislation and enforced motorcycle helmet use, but the helmet use rate stayed low as of 2005 Dinh VH, et al. [9].

Method

Data Sources and Data Items

To obtain the traffic-related fatalities, all deaths in Lang Son Province between January 2005 and December 2018 (missing data 2009-2010) were listed based on an official form referred to as the A6. Form A6 is collected according to decision No. 2554/2002/ QD-BYT of the Ministry of Health to register all causes of deaths in the community. Thereby, the registration process was reviewed monthly for each fatal case by the commune health stations (a total of 200 communes). The completeness, sensitivity, and specificity of the A6 system were reported as 93.9%, 75.4%, and 98.4%, respectively Stevenson M, et al. 2012. Based on form A6, all accidentrelated deaths were identified. To evaluate the completeness and the accuracy of the list, all accidents related deaths were compared with the register at the Center of Disease Control of Lang Son Province.
To improve the accuracy in identifying the cause of death, each case was reviewed by trained researchers to confirm any underlying causes of death. All cases with unclear causes were listed and then feedback to the corresponding commune health centers to clarify and confirm the cause of death. If a decision was not obtained, trained researchers would call the deceased’s relatives to identify the underlying cause of death. All underlying causes of death were coded following ICD-10. Then, traffic-related fatalities were extracted based on ICD-10 codes (V01-V89). Additionally, the deceased’s information of age, gender, date of death, and the average population of their commune in the corresponding year was collected based on designed data collection forms. Guidelines on how to determine the underlying cause of death and methods to collect data were sent to each commune health station, annually, for data collection.

Data Analysis

First, the crude death rate per 100,000 person-years was estimated. To estimate the age-standardized mortality rate per 100,000 person-years, we applied the accurate statistical data from the World Health Organization standard population for 2000- 2025. Mortality rates were described by year, sex, and age group to observe the trends and differences. Next, Poisson regression was used to estimate the mortality risk ratios (MRR) and 95% confidence interval (95%CI). The cut point of 0.05 of the p-value was considered statistically significant. The data were calculated using Stata version 13.0 (Stata Corp, College Station, Texas). Additional references can be found in the bibliography in the Appendix.

Results

Mortality Caused by Road Traffic Injuries Total Both Sexes

A total of 1841 deaths were identified by the A6 system, which consisted of 1542 and 299 deaths of men and women, respectively. Lang Son province experienced a crude mortality rate of 20.3 per 100.000 person-years from 2005-2018. All mortality indexes in men were higher than that in women. In terms of age, death cases were most prevalent among those aged under 70 years in both sexes. Overall, the estimated proportion of death cases under 70 years of age was as high as 94%, with 96% in men and 84% in women (Table 1). The overall proportion of deaths in both genders due to road traffic injuries was 3.74% (1,841 cases of road traffic injuries vs. 49,253 total cases). Mortality rates from 2005 to 2018 averaged around an approximate value of 20, with the highest in 2011 and the lowest in 2008.

Combining all death cases from 2005 to 2018, the overall agestandardized mortality rate, according to WHO-ASR, was 20.1 per 100.000 person-years. The number of death cases grew gradually from 2005 (148) to 2007 (164), followed by a sharp decrease in the 2007-2008 period (114). It could be explained by the fact that in 2007, the Vietnamese government passed legislation to force helmet wearing for all users of motorcycles, which was the most widely used personal transport in Viet Nam. However, mortality due to injuries in traffic accidences rose drastically between 2011 and 2013 and varied greatly from 2013 onwards. From 2005 to 2018, the adjusted MRR per year increment demonstrated a slight decline (0.991, 95% CI 0.980, 1.001). This declining trend was, however, non-significant (p = 0.093). The proportion of deaths under 70-year-old was notably high and was consistently above 90% in all years (Table 2).

Mortality Due to Road Traffic Injuries in Men

The estimated proportion of deaths due to road traffic injuries was 4.93% (1,542 cases of road traffic injuries vs. 31,262 total cases) in men. The crude mortality rate varied greatly from a low of 25.2 to as high as 46.4 deaths per 100.000 person-years in 2008 and 2011, respectively. When combining all cases from 2005 to 2018, the age-standardized mortality rate per 100.000 personyears by the WHO-ASR was 33.9. Like the overall trend, male deaths increased from 2005 to 2007 and experienced a sharp decline during the 2007-2008 period, followed by an elevated number of deaths from 2008 onwards. This fluctuation was attributed to the introduction of the helmet-wearing laws in 2007. The per-year increment MRR showed a non-significant declining trend (MRR (95% CI): 0.992 (0.980, 1.003), p=0.158). The proportion of deaths among men under the age of 70 was exceptionally high and was above 95% in almost all the years given (Table 3).

Mortality Due to Road Traffic Injuries in Women

The estimated proportion of deaths due to road traffic injuries was 1.66% (299 cases of road traffic injuries vs. 17,990 total cases) in women. Great variability was noticed within the crude mortality rate and MRR value across different years. However, this change in women was regarded as non-significant (Per-year increment MRR (95% CI): 0.987 (0.961, 1.014), p=0.335), which was similar to the mortality rate in men. After standardizing by age, according to WHO-ASR, the overall mortality rate was 6.7 per 100,000 personyears. Compared with men, the proportion of deaths in women under 70 was lower in general and fluctuated between 74.1 in 2013 and up to 94.1 in 2018 (Table 4).

Age-Specific Mortality Rate

Figure 1 illustrates the trend in the age-strata mortality rate by sex between 2005 and 2018 with the exclusion of 2009-2010 data due to missing reports. Overall, the mortality rate was highest among the 20-29 age group (34.7 deaths per 100.000 personyears), followed by the 70-79 age group (29.3 deaths per 100.000 person-years) and 80+ age group (26.5 deaths per 100.000 personyears). Men accounted for most of the death cases due to injuries by traffic incidences. The death rate in men was highest among the 20-29 age group (59.9 deaths per 100.000 person-years) and remained steadily high (above 30%) from 30-39 age group and older, whereas in females, the rate reached a peak at 70-79 age group (21.9 deaths per 100.000 person-years).

Discussion

This is the first study to assess the impact of helmet legislation on mortality related to RTC in Lang Son, a mountainous province in Viet Nam. Data were derived from the national health report system in this province under the A6 form. The present study indicated a slightly decreasing trend in road traffic mortality, but it was not statistically significant, after implementing the mandatory motorcycle helmet law. Although most deaths were aged under 70 years old, differences in ages were observed between the sexes. This study found that helmet law in 2007 reduced road traffic mortality from 2007 to 2008, which was statistically significant. However, between 2011 and 2018 there was only a slight decline, and it is seen as non-significant statistically. The efficacy of the mandatory helmet laws was far from expectation in the mountainous area of Lang Son, specifically. The introduction of helmet wearing laws has been proven to enhance road safety, according to studies in countries neighboring Viet Nam Chiu WT, et al. [4,5], and largescale studies both at the national Passmore JW, et al. [2,6,7], and provincial level Ha NT, et al. [8]. However, after 2007, the RTIsrelated death number in Lang Son province showed a slight yet non-significant declining trend among male and female road users.
One study by Ha et al. showed that more severe traffic injuries, including head injuries, were documented during the post-law period Ha NT, et al. [8], which raises questions about the quality of helmets used in the examined region. Using cheap helmets with poor quality and incorrect helmet wearing is common in Viet Nam Passmore JW, et al. [2,10]. Self-awareness of helmet use was also likely to be affected by social norms, safety beliefs, education, and awareness of traffic rules, which are distinctive for each geographical region Phung D, et al. [7], Urie Y, et al. 2016. A review study in Greece proved that the major reasons for noncompliance with the wearing of seat belts and helmets were education and culture Chliaoutakis JE, et al. [11]. Another study in Iran indicated that awareness of traffic legislation and enhancement of safety training towards motorcyclists was the key to helmet use Haqverdi MQ, et al. [12]. Additionally, rural areas might have more RTIs and RTIs-related deaths than modernized areas because of many environmental and cultural factors Chliaoutakis JE, et al. [11,13]. The majority of drivers in mountainous areas are unlicensed and underage Jiang B, et al. [13], which was also regarded as a result of a lack of compliance and policing of the laws. Distance from qualified medical emergency centers was another problem in remote areas, resulting in more deaths as traffic injuries were not treated properly and promptly Jiang B, et al. [13].
The present study also shows that fatalities due to road traffic injuries in men were higher than in women, as reported by previous author’s studies Chiu WT, et al. [4,14,15]. Many studies indicated that alcohol use increases risk among drivers Borges G, et al. [16,17]. In particular, alcohol use was a factor because of the drinking culture in Viet Nam Lincoln M [18]. A study in rural areas of the North of Viet Nam reported that the prevalence of alcohol consumption was 66% among men and 5% among women, respectively Kim BG, et al. [19]. This study has revealed that mortality in men was highest among the 20-29 age group as they are likely to have traffic-related habits, such as risky driving behavior and alcohol consumption Papadakaki M, et al. [20]. Nonetheless, the death rates from 30 to 80+ years of age remained consistently high, irrespective of age group. In contrast, RTIs among females were most prevalent towards the later age group of 70-79. The elderly female population is considered as vulnerable road users. They rarely participated in traffic as direct vehicle users due to the inability to operate a vehicle safely, requiring both physical and mental capability for immediate decisions whilst driving Kim SC, et al. [19].
This study has several limitations. First, the quality of data was unable to be validated due to the nature of secondary data, in particular, such as deaths without reporting by deceased’s relatives. However, the A6 system was proven to be highly reliable for road injury studies Stevenson M et al. 2015; Stevenson M et al. 2012. Secondly, the impact of other factors that may influence mortality rates, such as the availability and readiness, and the quality of the health care system, were not considered, which may distort the findings. However, the present study also suggested a hypothesis regarding the impact of mandatory motorcycle helmet laws on the trend of traffic-related mortality in a mountainous area in Viet Nam. Thirdly, missing data from 2009 to 2010 might not reflect the true effectiveness of helmet-wearing laws implemented in 2007.

Conclusion

The RTIs related annual mortality in Lang Son province decreased slightly but was statistically non-significant, indicating that helmet law implementation in 2007 had little impact on the overall death rates in this area. Therefore, further in-depth studies need to be considered to comprehensively assess the impact of helmet law on death-reducing outcomes in mountainous areas, including feasibility, acceptability, and sustainability.

Acknowledgment

The authors would like to thank the staff of 200 commune health stations for the time and effort they devoted to this study.

Disclosure Statement

There are no conflicts to disclose.

Author Contributors

All authors reviewed the manuscript and contributed revision many times. TTTD, LHP, LVN, NVT, and LTN were mainly responsible for drafting, revision, and analytic data. LHP, LVN, and NVT were principally responsible for data collection. TTTD and LTN extracted data and were mainly responsible for managing and analyzing data. All authors approved the version for publication.

Figure 1: Age-specific mortality rate per 100,000 person-years by sex during 2005-2018 (missing 2009-2010) due to road traffic injury.

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