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Manjarrez E, Delfin EF, Dominguez-Nicolas SM, Flores A. Power spectral density and similarity analysis of COVID-19 mortality waves across countries. Heliyon 2024; 10:e35546. [PMID: 39170280 PMCID: PMC11336732 DOI: 10.1016/j.heliyon.2024.e35546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 07/29/2024] [Accepted: 07/31/2024] [Indexed: 08/23/2024] Open
Abstract
Background During the COVID-19 pandemic, the Johns Hopkins University Center for Systems Science and Engineering (CSSE) established a comprehensive database detailing daily mortality rates across countries. This dataset revealed fluctuating global mortality trends attributable to COVID-19; however, the specific differences and similarities in mortality patterns between countries remain insufficiently explored. Consequently, this study employs Fourier and similarity analyses to examine these patterns within the frequency domain, thereby offering novel insights into the dynamics of COVID-19 mortality waves across different nations. Methods We employed the Fast Fourier transform to calculate the power spectral density (PSD) of COVID-19 mortality waves in 199 countries from January 22, 2020, to March 9, 2023. Moreover, we performed a cosine similarity analysis of these PSD patterns among all the countries. Results We identified two dominant peaks in the grand averaged PSD: one at a frequency of 1.15 waves per year (i.e., one wave every 10.4 months) and another at 2.7 waves per year (i.e., one wave every 4.4 months). We also found a cosine similarity index distribution with a skewness of -0.54 and a global median of cosine similarity index of 0.84, thus revealing a remarkable similarity in the dominant peaks of the COVID-19 mortality waves. Conclusion These findings could be helpful for planetary health if a future pandemic of a similar scale occurs so that effective confinement measures or other actions could be planned during these two identified periods.
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Affiliation(s)
- Elias Manjarrez
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, 14 Sur 6301, Colonia San Manuel, Apartado Postal 406, CP 72570, Puebla, Puebla, Mexico
| | - Erick F. Delfin
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, 14 Sur 6301, Colonia San Manuel, Apartado Postal 406, CP 72570, Puebla, Puebla, Mexico
| | - Saul M. Dominguez-Nicolas
- Centro de Investigación de Micro y Nanotecnología, Universidad Veracruzana, Calzada Ruiz Cortines 455, Boca del Rio, Veracruz, 94294, Mexico
- Facultad de Ingeniería Eléctrica y Electrónica, Universidad Veracruzana, Calzada Ruiz Cortines 455, Boca del Rio, Veracruz, 94294, Mexico
| | - Amira Flores
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, 14 Sur 6301, Colonia San Manuel, Apartado Postal 406, CP 72570, Puebla, Puebla, Mexico
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Hines JZ, Kapombe P, Mucheleng’anga A, Chanda SL, Hamukale A, Cheelo M, Kamalonga K, Tally L, Monze M, Kapina M, Agolory S, Auld AF, Lungu P, Chilengi R. COVID-19 mortality sentinel surveillance at a tertiary referral hospital in Lusaka, Zambia, 2020-2021. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0003063. [PMID: 38551924 PMCID: PMC10980196 DOI: 10.1371/journal.pgph.0003063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 03/06/2024] [Indexed: 04/01/2024]
Abstract
Deaths from COVID-19 likely exceeded official statistics in Zambia because of limited testing and incomplete death registration. We describe a sentinel COVID-19 mortality surveillance system in Lusaka, Zambia. We analyzed surveillance data on deceased persons of all ages undergoing verbal autopsy (VA) and COVID-19 testing at the University Teaching Hospital (UTH) mortuary in Lusaka, Zambia, from April 2020 through August 2021. VA was done by surveillance officers for community deaths and in-patient deaths that occurred <48 hours after admission. A standardized questionnaire about the circumstances proximal to death was used, with a probable cause of death assigned by a validated computer algorithm. Nasopharyngeal specimens from deceased persons were tested for COVID-19 using polymerase chain reaction and rapid diagnostic tests. We analyzed the cause of death by COVID-19 test results. Of 12,919 deceased persons at UTH mortuary during the study period, 5,555 (43.0%) had a VA and COVID-19 test postmortem, of which 79.7% were community deaths. Overall, 278 (5.0%) deceased persons tested COVID-19 positive; 7.1% during waves versus 1.4% during nonwave periods. Most (72.3%) deceased persons testing COVID-19 positive reportedly had fever, cough, and/or dyspnea and most (73.5%) reportedly had an antemortem COVID-19 test. Common causes of death for those testing COVID-19 positive included acute cardiac disease (18.3%), respiratory tract infections (16.5%), other types of cardiac diseases (12.9%), and stroke (7.2%). A notable portion of deceased persons at a sentinel site in Lusaka tested COVID-19 positive during waves, supporting the notion that deaths from COVID-19 might have been undercounted in Zambia. Many had displayed classic COVID-19 symptoms and been tested before death yet nevertheless died in the community, potentially indicating strained medical services during waves. The high proportion of cardiovascular diseases deaths might reflect the hypercoagulable state during severe COVID-19. Early supportive treatment and availability of antivirals might lessen future mortality.
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Affiliation(s)
- Jonas Z. Hines
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | | | | | | | - Amos Hamukale
- Zambia National Public Health Institute, Lusaka, Zambia
| | | | | | - Leigh Tally
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | - Mwaka Monze
- University Teaching Hospital, Lusaka, Zambia
| | - Muzala Kapina
- Zambia National Public Health Institute, Lusaka, Zambia
| | - Simon Agolory
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | - Andrew F. Auld
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | | | - Roma Chilengi
- Zambia National Public Health Institute, Lusaka, Zambia
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Levi R, Zerhouni EG, Altuvia S. Predicting the spread of SARS-CoV-2 variants: An artificial intelligence enabled early detection. PNAS NEXUS 2024; 3:pgad424. [PMID: 38170049 PMCID: PMC10759796 DOI: 10.1093/pnasnexus/pgad424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 11/27/2023] [Indexed: 01/05/2024]
Abstract
During more than 3 years since its emergence, SARS-CoV-2 has shown great ability to mutate rapidly into diverse variants, some of which turned out to be very infectious and have spread throughout the world causing waves of infections. At this point, many countries have already experienced up to six waves of infections. Extensive academic work has focused on the development of models to predict the pandemic trajectory based on epidemiological data, but none has focused on predicting variant-specific spread. Moreover, important scientific literature analyzes the genetic evolution of SARS-CoV-2 variants and how it might functionally affect their infectivity. However, genetic attributes have not yet been incorporated into existing epidemiological modeling that aims to capture infection trajectory. Thus, this study leverages variant-specific genetic characteristics together with epidemiological information to systematically predict the future spread trajectory of newly detected variants. The study describes the analysis of 9.0 million SARS-CoV-2 genetic sequences in 30 countries and identifies temporal characteristic patterns of SARS-CoV-2 variants that caused significant infection waves. Using this descriptive analysis, a machine-learning-enabled risk assessment model has been developed to predict, as early as 1 week after their first detection, which variants are likely to constitute the new wave of infections in the following 3 months. The model's out-of-sample area under the curve (AUC) is 86.3% for predictions after 1 week and 90.8% for predictions after 2 weeks. The methodology described in this paper could contribute more broadly to the development of improved predictive models for variants of other infectious viruses.
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Affiliation(s)
- Retsef Levi
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - El Ghali Zerhouni
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Shoshy Altuvia
- Department of Microbiology and Molecular Genetics, The Hebrew University-Hadassah Medical School, Jerusalem, 9112102, Israel
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Chapman LAC, Aubry M, Maset N, Russell TW, Knock ES, Lees JA, Mallet HP, Cao-Lormeau VM, Kucharski AJ. Impact of vaccinations, boosters and lockdowns on COVID-19 waves in French Polynesia. Nat Commun 2023; 14:7330. [PMID: 37957160 PMCID: PMC10643399 DOI: 10.1038/s41467-023-43002-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
Estimating the impact of vaccination and non-pharmaceutical interventions on COVID-19 incidence is complicated by several factors, including successive emergence of SARS-CoV-2 variants of concern and changing population immunity from vaccination and infection. We develop an age-structured multi-strain COVID-19 transmission model and inference framework to estimate vaccination and non-pharmaceutical intervention impact accounting for these factors. We apply this framework to COVID-19 waves in French Polynesia and estimate that the vaccination programme averted 34.8% (95% credible interval: 34.5-35.2%) of 223,000 symptomatic cases, 49.6% (48.7-50.5%) of 5830 hospitalisations and 64.2% (63.1-65.3%) of 1540 hospital deaths that would have occurred in a scenario without vaccination up to May 2022. We estimate the booster campaign contributed 4.5%, 1.9%, and 0.4% to overall reductions in cases, hospitalisations, and deaths. Our results suggest that removing lockdowns during the first two waves would have had non-linear effects on incidence by altering accumulation of population immunity. Our estimates of vaccination and booster impact differ from those for other countries due to differences in age structure, previous exposure levels and timing of variant introduction relative to vaccination, emphasising the importance of detailed analysis that accounts for these factors.
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Affiliation(s)
- Lloyd A C Chapman
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
- Department of Mathematics and Statistics, Lancaster University, Lancaster, UK.
| | - Maite Aubry
- Laboratoire de recherche sur les infections virales émergentes, Institut Louis Malardé, Tahiti, French Polynesia
| | - Noémie Maset
- Cellule Epi-surveillance Plateforme COVID-19, Tahiti, French Polynesia
| | - Timothy W Russell
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Edward S Knock
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - John A Lees
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Cambridgeshire, UK
| | | | - Van-Mai Cao-Lormeau
- Laboratoire de recherche sur les infections virales émergentes, Institut Louis Malardé, Tahiti, French Polynesia
| | - Adam J Kucharski
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Laboratoire de recherche sur les infections virales émergentes, Institut Louis Malardé, Tahiti, French Polynesia
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Samaan F, Freitas RAP, Viana R, Gâmbaro L, Cunha K, Vieira TD, Feitosa V, Correa EA, Maciel AT, Aranha S, Osawa EA, Pillar R, Flato EMDS, da Silva RC, Carneiro E, Souza FBGDL, Rossi PRG, Abud MB, Konigsfeld HP, da Silva RG, de Souza RBC, Coutinho SM, Goes MÂ, da Silva BAB, Zanetta DMT, Burdmann EA. Critically ill patients with COVID-19-associated acute kidney injury treated with kidney replacement therapy: Comparison between the first and second pandemic waves in São Paulo, Brazil. PLoS One 2023; 18:e0293846. [PMID: 37922282 PMCID: PMC10624321 DOI: 10.1371/journal.pone.0293846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/20/2023] [Indexed: 11/05/2023] Open
Abstract
INTRODUCTION This study aimed to compare the characteristics and outcomes of critically ill patients with COVID-19-associated acute kidney injury (AKI) who were treated with kidney replacement therapy (KRT) in the first and second waves of the pandemic in the megalopolis of Sao Paulo, Brazil. METHODS A multicenter retrospective study was conducted in 10 intensive care units (ICUs). Patients aged ≥18 years, and treated with KRT due to COVID-19-associated AKI were included. We compared demographic, laboratory and clinical data, KRT parameters and patient outcomes in the first and second COVID-19 waves. RESULTS We assessed 656 patients (327 in the first wave and 329 in the second one). Second-wave patients were admitted later (7.1±5.0 vs. 5.6±3.9 days after the onset of symptoms, p<0.001), were younger (61.4±13.7 vs. 63.8±13.6 years, p = 0.023), had a lower frequency of diabetes (37.1% vs. 47.1%, p = 0.009) and obesity (29.5% vs. 40.0%, p = 0.007), had a greater need for vasopressors (93.3% vs. 84.6%, p<0.001) and mechanical ventilation (95.7% vs. 87.8%, p<0.001), and had higher lethality (84.8% vs. 72.7%, p<0.001) than first-wave patients. KRT quality markers were independently associated with a reduction in the OR for death in both pandemic waves. CONCLUSIONS In the Sao Paulo megalopolis, the lethality of critically ill patients with COVID-19-associated AKI treated with KRT was higher in the second wave of the pandemic, despite these patients being younger and having fewer comorbidities. Potential factors related to this poor outcome were difficulties in health care access, lack of intra-hospital resources, delay vaccination and virus variants.
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Affiliation(s)
- Farid Samaan
- Grupo Hapvida-NotreDame Intermédica, São Paulo, SP, Brazil
- Instituto Dante Pazzanese de Cardiologia, São Paulo, SP, Brazil
- Secretaria de Estado da Saúde de São Paulo, São Paulo, SP, Brazil
| | | | - Renata Viana
- Instituto Dante Pazzanese de Cardiologia, São Paulo, SP, Brazil
| | - Lívia Gâmbaro
- Instituto Dante Pazzanese de Cardiologia, São Paulo, SP, Brazil
| | - Karlla Cunha
- Grupo Hapvida-NotreDame Intermédica, São Paulo, SP, Brazil
| | | | | | | | | | - Sylvia Aranha
- Imed Research Group, Hospital São Camilo Pompéia, São Paulo, SP, Brazil
| | | | - Roberta Pillar
- Unidade Assistencial Hospital Ipiranga, São Paulo, SP, Brazil
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Emmanuel Almeida Burdmann
- Laboratório de Investigação Médica (LIM 12), Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
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Cassell CH, Raghunathan PL, Henao O, Pappas-DeLuca KA, Rémy WL, Dokubo EK, Merrill RD, Marston BJ. Global Responses to the COVID-19 Pandemic. Emerg Infect Dis 2022; 28:S4-S7. [PMID: 36502408 DOI: 10.3201/eid2813.221733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
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