Assessment of the recycling potential of valuable metals by mapping the elemental composition in discarded light-emitting diodes (LEDs).

Electronic waste (e-waste) is the world's fastest-growing type of waste, with lighting accounting for 9% of the total. Light-emitting diodes (LEDs) are composed of the most concentrated critical elements (Ag and Au) and recovery of these metals could generate economic benefits and reduce the burdens of environmental pollution; nevertheless, the absence of information about their composition currently presents a challenge in recycling these metals with minimal prospects for recovery. This study assessed the distribution and variation of elemental concentrations of 16 different elements in three generations of LEDs (12 different LED units): sub-mounted-device (SMD #10), chip-on-board (COB #1), and positive-intrinsic-negative (PIN #1). The SMD LEDs contained a considerable amount of Au with a median average concentration of 1204 mg/kg (ranging from 323 - 3687 mg/kg), which was similar to that of COB (1550 mg/kg), but higher than that of PIN LED (175 mg/kg). Based on the total threshold limiting concentration (TTLC), the Cu levels (605,823 mg/kg) in the SMD package exceeded the regulatory limits (2500 mg/kg). Concentrations of the hazardous elements Cr (29 mg/kg), Pb (12 mg/kg), Cd (0.1 mg/kg), and As (1 mg/kg) in the LED packages were within the regulatory limits. To recycle precious metals and other technological metals, a well-organized and dedicated optimized assessment of the value of metals is required especially in accordance with the concept of criticality and recyclability. Two factors, i.e., a high resource index (RI) and technology index (TI), suggest the importance of waste to the economy and has a significant potential for recycling with less processing burdens. Present findings indicated that the COB and a few of the studied SMD LEDs (3020, 4014, 5630, and 7020), exhibit high criticality and recyclability. For the RI and TI index, the contribution of metals such as Cu, Fe, Al, and Au were dominant. These findings can serve as a reference for the development of a viable approach for the recycling and recovery of targeted metals from LED e-waste.

Combining serology with case-detection, to allow the easing of restrictions against SARS-CoV-2: a modelling-based study in India.

India's lockdown and subsequent restrictions against SARS-CoV-2, if lifted without any other mitigations in place, could risk a second wave of infection. A test-and-isolate strategy, using PCR diagnostic tests, could help to minimise the impact of this second wave. Meanwhile, population-level serological surveillance can provide valuable insights into the level of immunity in the population. Using a mathematical model, consistent with an Indian megacity, we examined how seroprevalence data could guide a test-and-isolate strategy, for fully lifting restrictions. For example, if seroprevalence is 20% of the population, we show that a testing strategy needs to identify symptomatic cases within 5-8 days of symptom onset, in order to prevent a resurgent wave from overwhelming hospital capacity in the city. This estimate is robust to uncertainty in the effectiveness of the lockdown, as well as in immune protection against reinfection. To set these results in their economic context, we estimate that the weekly cost of such a PCR-based testing programme would be less than 2.1% of the weekly economic loss due to the lockdown. Our results illustrate how PCR-based testing and serological surveillance can be combined to design evidence-based policies, for lifting lockdowns in Indian cities and elsewhere.

Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models.

BACKGROUND: The post-2015 End TB Strategy sets global targets of reducing tuberculosis incidence by 50% and mortality by 75% by 2025. We aimed to assess resource requirements and cost-effectiveness of strategies to achieve these targets in China, India, and South Africa. METHODS: We examined intervention scenarios developed in consultation with country stakeholders, which scaled up existing interventions to high but feasible coverage by 2025. Nine independent modelling groups collaborated to estimate policy outcomes, and we estimated the cost of each scenario by synthesising service use estimates, empirical cost data, and expert opinion on implementation strategies. We estimated health effects (ie, disability-adjusted life-years averted) and resource implications for 2016-35, including patient-incurred costs. To assess resource requirements and cost-effectiveness, we compared scenarios with a base case representing continued current practice. FINDINGS: Incremental tuberculosis service costs differed by scenario and country, and in some cases they more than doubled existing funding needs. In general, expansion of tuberculosis services substantially reduced patient-incurred costs and, in India and China, produced net cost savings for most interventions under a societal perspective. In all three countries, expansion of access to care produced substantial health gains. Compared with current practice and conventional cost-effectiveness thresholds, most intervention approaches seemed highly cost-effective. INTERPRETATION: Expansion of tuberculosis services seems cost-effective for high-burden countries and could generate substantial health and economic benefits for patients, although substantial new funding would be required. Further work to determine the optimal intervention mix for each country is necessary. FUNDING: Bill & Melinda Gates Foundation.

Transmission modeling and health systems: the case of TB in India.

BACKGROUND: TB in India presents the challenges of a complex disease in a complex healthcare system. Mathematical models, offering a framework for capturing such complexities, have proven useful in exploring strategies for the control of TB. As the use of such techniques develops in future, it is important to understand what aspects of the healthcare system are most critical for models to faithfully capture. METHODS: We ask what type of intervention should be prioritized for the control of TB, amongst: improved diagnosis of TB per visit to a healthcare provider; improved treatment success; and increased identification of TB cases in the community? Using simple mathematical models, calibrated to the national TB epidemic in India, we explore how the relative importance of each of these interventions is affected by different assumptions for the patient pathway in careseeking, thus outlining aspects of the healthcare system that may matter most for the transmission dynamics of TB. RESULTS: We illustrate that, under a range of plausible parameter assumptions, it is possible to generate conditions under which a case-finding intervention would be prioritized over improvement of diagnosis and treatment, and vice versa. Key data needs include: the proportion of patients not contacting the healthcare system, and the mean patient delay before first seeking care. CONCLUSIONS: For mathematical models addressing strategic priorities for TB control, it is important to adequately quantify the dynamics of careseeking. We outline ways in which these data gaps may be addressed, and questions for future work.