Insight into Delta variant dominated second wave of COVID-19 in Nepal

Adhikari, Khagendra; Gautam, Ramesh; Pokharel, Anjana; Dhimal, Meghnath; Uprety, Kedar Nath; Vaidya, Naveen K.

doi:10.1016/j.epidem.2022.100642

Cited by 12 publications

(7 citation statements)

References 40 publications

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“…In the South Asian region, the first wave was comparatively less severe than the subsequent waves [24]. The second wave in Nepal was predominantly caused by the COVID-19 Delta variant (B.1.617.2), which was more virulent than the variants of SARS-CoV-2 that caused that first wave [25,26]. Additionally, the population may have been more complacent during the second wave.…”

Section: Discussionmentioning

confidence: 99%

Epidemiology of COVID‐19 mortality in Nepal: An analysis of the National Health Emergency Operation Center data

Adhikari,

Ranabhat,

Bhattarai

et al. 2023

Public Health Challenges

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IntroductionCOVID‐19 had caused nearly 12,000 deaths in Nepal by March 2023. In this study, we compare COVID‐19‐associated mortality in the first (September 15 to November 30, 2020) and second (April 15 to June 30, 2021) waves of the pandemic in Nepal and investigate the associated epidemiological factors.MethodsWe disaggregated the COVID‐19‐related deaths between the first and second waves of the pandemic using the national COVID‐19 database and evaluated the association of independent variables with the deaths in the first versus second waves.ResultsOut of 8133 deaths, 25% died in the first wave and 75% in the second. Overall, 33.5% of the deceased were female, and 52% of the deaths were in those 60 years or older. A vast majority (92%) of deaths occurred in hospitals. Geographically, the middle “Hill” region (58.3%) witnessed the most significant number of deaths. About two thirds (64%) had at least one comorbid condition. Multivariable logistic regression showed a difference in the reported deaths by province (state) and geography (ecological region) between the first and second waves. Those in the age groups “19–39 years” and “40–59 years” were more likely to die in the second wave than in the first wave compared to the younger age group.ConclusionsOverall, deaths were concentrated among older age groups, males, in the Hill regions, in the western provinces, and those with comorbidities. Therefore, the country must focus on these areas to ensure an efficient and effective pandemic response in the future.

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Section: Discussionmentioning

confidence: 99%

Epidemiology of COVID‐19 mortality in Nepal: An analysis of the National Health Emergency Operation Center data

Adhikari,

Ranabhat,

Bhattarai

et al. 2023

Public Health Challenges

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“…We also incorporated information on SARS-CoV-2 vaccination in the Dominican Republic, using data collated by Our World in Data (10). Fully vaccinated individuals moved to a vaccinated model compartment (V) from which, subject to vaccine waning parameters, they can move to the exposed state (E) or directly to a sub-clinical infection (I s ).…”

Section: Methodsmentioning

confidence: 99%

“…Mathematical models have been used throughout the pandemic to provide decision-support to policy makers through estimation of key epidemiological parameters, forecasts of future incidence, projections of epidemic trajectories under different scenarios, and quantification of the impact of non-pharmaceutical interventions. However, despite regular and in-depth modelling decision-support for high-income countries, there has been a lack of equivalent modelling analysis to understand transmission and control in low-and middle-income countries (9)(10)(11)(12)(13)(14)(15). To address this gap, we used an age-structured transmission dynamic model to quantify the drivers of epidemic dynamics in the Dominican Republic during the first two years of the pandemic, and to assess the impact of the vaccination campaign on COVID-19 hospitalisations and deaths.…”

Section: Introductionmentioning

confidence: 99%

Modelling the impact of population mobility, post-infection immunity and vaccination on SARS-CoV-2 transmission in the Dominican Republic

Finch,

Nilles,

Paulino

et al. 2023

Preprint

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COVID-19 epidemic dynamics are driven by a complex interplay of factors including population behaviour, government interventions, new variants, vaccination campaigns and immunity from prior infections. We aimed to quantify the epidemic drivers of SARS-CoV-2 dynamics in the Dominican Republic, an upper-middle income country of 10.8 million people, and assess the impact of the vaccination campaign implemented in February 2021 in saving lives and averting hospitalisations. We used an age-structured, multi-variant transmission dynamic model to characterise epidemic drivers in the Dominican Republic and explore counterfactual scenarios around vaccination coverage and population mobility. We fit the model to reported deaths, hospital bed occupancy, ICU bed occupancy and seroprevalence data until December 2021 and simulated epidemic trajectories under different counterfactual vaccination scenarios. We estimate that vaccination averted 5040 hospital admissions (95% CrI: 4750 - 5350), 1500 ICU admissions (95% CrI: 1420 - 1590) and 544 deaths (95% CrI: 488 - 606) in the first 6 months of the campaign. We also found that early vaccination with Sinovac-CoronaVac was preferable to delayed vaccination using a product with higher efficacy. We investigated the trade-off between changes in vaccination coverage and population mobility to understand how much relaxation of social distancing measures vaccination was able to 'buy' in the later stages of a pandemic. We found that if no vaccination had occurred, an additional decrease of 10-20% in population mobility would have been required to maintain the same death and hospitalisation outcomes. We found SARS-CoV-2 transmission dynamics in the Dominican Republic were driven by substantial accumulation of immunity during the first two years of the pandemic but that, despite this, vaccination was essential in enabling a return to pre-pandemic mobility levels without incurring considerable additional morbidity and mortality.

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“…One limitation is the constantly evolving nature of the pandemic. In the months that followed data collection, Nepal was hit with the devastating Delta wave (Akhikari et al, 2022). The government of Nepal responded with another lockdown beginning in late April and lasting 4 months.…”

Section: Context and Samplementioning

confidence: 99%

Coping with COVID‐19 shocks in rural Nepal

Ekstrom,

Janzen,

Magnan

2023

Applied Eco Perspectives Pol

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We examine shocks experienced by rural Nepali households during the COVID‐19 pandemic. Households primarily experienced income and price shocks during a government‐imposed lockdown. During this time, households managed to effectively protect consumption, and mostly relied on credit (26%), asset sales (10%) and savings (8%). Debt levels nearly doubled, with limited changes to savings. We then leverage a long‐term randomized control trial (RCT) to assess whether beneficiaries of a livestock livelihood program are more resilient. Program beneficiaries are 6 percentage points less likely to take out new loans.

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Insight into Delta variant dominated second wave of COVID-19 in Nepal

Cited by 12 publications

References 40 publications

Epidemiology of COVID‐19 mortality in Nepal: An analysis of the National Health Emergency Operation Center data

Epidemiology of COVID‐19 mortality in Nepal: An analysis of the National Health Emergency Operation Center data

Modelling the impact of population mobility, post-infection immunity and vaccination on SARS-CoV-2 transmission in the Dominican Republic

Coping with COVID‐19 shocks in rural Nepal

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