The COVID-19 pandemic, declared by the WHO in March 2020, necessitated stringent lockdowns globally to curb transmission. However, prolonged lockdowns are unsustainable, impacting economies and livelihoods, particularly in low-income countries (LICs) like Nepal. This study addresses the need for an evidence-based, multidisciplinary approach to risk assessment and communication to optimize decision-making during the pandemic. Effective risk communication, by accurately informing individuals and communities about their risk levels, can encourage appropriate public health measures, reduce fear, and promote informed decision-making, ultimately facilitating a balanced approach between pandemic control and maintaining economic activity. The study aims to develop a framework for near real-time risk assessment to guide individuals and communities in mitigating the impact of COVID-19.

The literature review highlights the global impact of COVID-19, emphasizing the limitations of prolonged lockdowns and the psychological consequences of the pandemic. Studies on institutional and individual behavior influencing infectious disease spread are cited, along with reports on the economic uncertainties and vulnerabilities exacerbated by lockdowns in LICs. The review underscores the importance of balancing pandemic control with economic considerations and the need for personalized and spatial risk assessment to inform targeted interventions and facilitate the easing of lockdown measures.

The study proposes a framework for COVID-19 risk assessment incorporating various factors at individual and regional levels. **Data Sources:** Data from multiple sources were utilized, including published COVID-19 case data from China, Italy, Spain, Germany, the USA, and the UK to establish relationships between influential factors and mortality. Demographic, health condition, and facility data, socioeconomic data, and daily updates on COVID-19 cases and quarantines from Nepal's Ministry of Health and Population were also used. The political boundary data for Nepal was obtained from the Survey Department, Nepal. **Personal Risk Assessment:** This component comprises three aspects: individual vulnerability, risk of infection (based on symptoms), and risk of transmission. Individual vulnerability is determined by age (modeled using an exponential relationship with mortality data), gender, and pre-existing health conditions (with relative risk factors derived from multiple datasets). The probability of infection is assessed using exposure (profession, activities, travel, contact with infected individuals) and regional risk. Symptom data from various studies is used to inform users regarding the possibility of infection and to advise contacting healthcare facilities. Exposure is calculated through professional roles and activities, and preventive measures such as mask usage, sanitization, and physical distancing reduce the exposure score. **Regional Risk Assessment:** This uses a multidisciplinary approach combining COVID-19 transmission risk (CTR), public health risk (PHR), and socioeconomic risk (SER) to generate an overall risk score. CTR is calculated using positive cases, quarantined individuals, community exposure (based on facilities like airports and hotels), and population density. PHR incorporates the prevalence of pre-existing health conditions and the availability of health facilities. SER considers poverty index, literacy rate, and water, sanitation, and hygiene (WASH) index. Regional importance is assessed based on food production and supply chain, separately mapped for better clarity. **COVIRA Tool:** The COVIRA web application integrates the framework, allowing users to input data via a questionnaire to obtain personal risk scores and access regional risk information. The risk scores are represented on a scale of 0-100 for all risk assessments. Qualitative risk levels (very low, low, moderate, high, very high) are mapped to the numerical scores for clearer communication.

COVIRA dynamically assesses regional and personal COVID-19 risk using the latest available data. Results are presented in three segments: personal risk, regional risk assessment, and zonal importance. **Personal Risk:** The personal risk model reveals that age and existing health conditions are significant risk factors for severe outcomes. An exponential relationship is found between age and mortality risk, and comorbidities significantly increase risk. A COVID Risk Index (CRI) is calculated, categorizing individuals into five risk levels based on CRI value ranges. **Regional Risk:** Regional risk maps for Nepal illustrate the overall risk and transmission risk. Kathmandu displays high risk, while areas with high transmission risk don't always correlate with high overall risk. Time series maps showing the progression of risk from May 10th to June 10th, 2020 are included. **Regional Importance:** A map highlights areas crucial for food production and supply chain. **COVIRA Tool:** The COVIRA tool generates personal and regional risk assessments based on user input and available data. It provides personalized risk levels and recommendations, along with access to local risk information. Mathematical equations, such as Equation 1 (relationship between age and mortality risk), Equation 2 (coefficient of comorbidity), Equation 3 (CRI calculation), Equation 4 (probability of infection), Equation 5 (CTR calculation), Equation 6 (PCS calculation), Equation 7 (PHR calculation), and Equation 8 (SER calculation) are provided in the original paper to illustrate the quantitative methodology employed.

The COVIRA framework demonstrates a multidisciplinary approach to COVID-19 risk assessment, effectively integrating individual and regional factors. The model's results show good agreement between predicted transmission risk and the actual case distribution. The regional risk maps can guide targeted interventions and support the prioritization of essential services, especially crucial during lockdowns in LICs. The ability to assess personal risk in real-time empowers individuals to make informed decisions, while regional assessments support policymaking and resource allocation. The model's adaptability makes it valuable for diverse contexts globally, enhancing preparedness for future pandemics.

The COVIRA framework and tool offer a valuable approach to COVID-19 risk assessment and communication, combining personal and regional risk assessments. The model's scalability and adaptability makes it a significant contribution to pandemic preparedness. Future research could explore expanding the model to include additional risk factors, refining the risk scoring system, and incorporating more diverse datasets to enhance its accuracy and applicability in various settings.

The study's reliance on data from high-income countries for some risk factor relationships might affect the generalizability to LICs with different healthcare systems and demographic characteristics. The accuracy of regional risk assessments depends on the quality and availability of data, potentially influenced by limitations in data collection or reporting in certain regions. User-input data for personal risk assessment may be subject to biases or inaccuracies, though this will affect only the individual score.