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1.
J Cancer Policy ; 33: 100340, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1882163

ABSTRACT

BACKGROUND: Early reports suggested that COVID-19 patients with cancer were at higher risk of COVID-19-related death. We conducted a systematic review with risk of bias assessment and synthesis of the early evidence on the risk of COVID-19-related death for COVID-19 patients with and without cancer. METHODS AND FINDINGS: We searched Medline/Embase/BioRxiv/MedRxiv/SSRN databases to 1 July 2020. We included cohort or case-control studies published in English that reported on the risk of dying after developing COVID-19 for people with a pre-existing diagnosis of any cancer, lung cancer, or haematological cancers. We assessed risk of bias using tools adapted from the Newcastle-Ottawa Scale. We used the generic inverse-variance random-effects method for meta-analysis. Pooled odds ratios (ORs) and hazard ratios (HRs) were calculated separately. Of 96 included studies, 54 had sufficient non-overlapping data to be included in meta-analyses (>500,000 people with COVID-19, >8000 with cancer; 52 studies of any cancer, three of lung and six of haematological cancers). All studies had high risk of bias. Accounting for at least age consistently led to lower estimated ORs and HRs for COVID-19-related death in cancer patients (e.g. any cancer versus no cancer; six studies, unadjusted OR=3.30,95%CI:2.59-4.20, adjusted OR=1.37,95%CI:1.16-1.61). Adjusted effect estimates were not reported for people with lung or haematological cancers. Of 18 studies that adjusted for at least age, 17 reported positive associations between pre-existing cancer diagnosis and COVID-19-related death (e.g. any cancer versus no cancer; nine studies, adjusted OR=1.66,95%CI:1.33-2.08; five studies, adjusted HR=1.19,95%CI:1.02-1.38). CONCLUSIONS: The initial evidence (published to 1 July 2020) on COVID-19-related death in people with cancer is characterised by multiple sources of bias and substantial overlap between data included in different studies. Pooled analyses of non-overlapping early data with adjustment for at least age indicated a significantly increased risk of COVID-19-related death for those with a pre-existing cancer diagnosis.

2.
J Cancer Policy ; 33: 100338, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1878231

ABSTRACT

BACKGROUND: The early COVID-19 literature suggested that people with cancer may be more likely to be infected with SARS-CoV-2 or develop COVID-19 than people without cancer, due to increased health services contact and/or immunocompromise. While some studies were criticised due to small patient numbers and methodological limitations, they created or reinforced concerns of clinicians and people with cancer. These risks are also important in COVID-19 vaccine prioritisation decisions. We performed a systematic review to critically assess and summarise the early literature. METHODS AND FINDINGS: We conducted a systematic search of Medline/Embase/BioRxiv/MedRxiv/SSRN databases including peer-reviewed journal articles, letters/commentaries, and non-peer-reviewed pre-print articles for 1 January-1 July 2020. The primary endpoints were diagnosis of COVID-19 and positive SARS-CoV-2 test. We assessed risk of bias using a tool adapted from the Newcastle-Ottawa Scale. Twelve studies were included in the quantitative synthesis. All four studies of COVID-19 incidence (including 24,181,727 individuals, 125,649 with pre-existing cancer) reported that people with cancer had higher COVID-19 incidence rates. Eight studies reported SARS-CoV-2 test positivity for > 472,000 individuals, 48,370 with pre-existing cancer. Seven of these studies comparing people with any and without cancer, were pooled using random effects [pooled odds ratio 0.91, 95 %CI: 0.57-1.47; unadjusted for age, sex, or comorbidities]. Two studies suggested people with active or haematological cancer had lower risk of a positive test. All 12 studies had high risk of bias; none included universal or random COVID-19/SARS-CoV-2 testing. CONCLUSIONS: The early literature on susceptibility to SARS-CoV-2/COVID-19 for people with cancer is characterised by pervasive biases and limited data. To provide high-quality evidence to inform decision-making, studies of risk of SARS-CoV-2/COVID-19 for people with cancer should control for other potential modifiers of infection risk, including age, sex, comorbidities, exposure to the virus, protective measures taken, and vaccination, in addition to stratifying analyses by cancer type, stage at diagnosis, and treatment received.

3.
Int J Environ Res Public Health ; 19(11)2022 May 26.
Article in English | MEDLINE | ID: covidwho-1869585

ABSTRACT

The COVID-19 pandemic had an unfavorable impact on overall mortality in Italy, with the strongest consequences in northern Italy. Scant data are available on cause-specific mortality. This study aims at investigating the impact of the pandemic on the overall and cause-specific mortality in one province in northern Italy, Pavia. We linked individual-level administrative data (i.e., death certification and population data) from the Health Protection Agency (HPA) in Pavia province between 2015 and 2020. We computed age-standardized mortality rates (Italian population 2011) by cause, sex, and calendar year, and computed the rate ratio and the corresponding 95% confidence intervals to compare rates in 2020 versus 2015-2019. The 2020 excess total mortality in Pavia was 24% in men and 25% in women, reaching rates of 1272.6/100,000 and 1304.4/100,000, respectively. Significant excesses were found for infectious and parasitic diseases, excluding COVID-19 (about +30% in both sexes); respiratory system diseases (44% in men; 30% in women); and dementia and Alzheimer's disease among men (24%). Reductions were reported for neoplasms (-14% in men); cerebrovascular diseases (-25% in men); and ischemic diseases (-13% in women), but also for transport accidents in men. COVID-19 was the third cause of death in both sexes with rates of 274.9/100,000 men (859 total deaths) and 213.9/100,000 women (758 total deaths). Excess mortality in Pavia was higher than Italy but lower than Lombardy. Increases in mortality from causes related to infectious and respiratory diseases can likely be explained by underdiagnosed deaths from COVID-19.


Subject(s)
COVID-19 , Neoplasms , Cause of Death , Female , Humans , Italy/epidemiology , Male , Mortality , Neoplasms/epidemiology , Pandemics
4.
Epidemics ; 37: 100528, 2021 12.
Article in English | MEDLINE | ID: covidwho-1520903

ABSTRACT

BACKGROUND: In the night of February 20, 2020, the first epidemic of the novel coronavirus disease (COVID-19) outside Asia was uncovered by the identification of its first patient in Lombardy region, Italy. In the following weeks, Lombardy experienced a sudden increase in the number of ascertained infections and strict measures were imposed to contain the epidemic spread. METHODS: We analyzed official records of cases occurred in Lombardy to characterize the epidemiology of SARS-CoV-2 during the early phase of the outbreak. A line list of laboratory-confirmed cases was set up and later retrospectively consolidated, using standardized interviews to ascertained cases and their close contacts. We provide estimates of the serial interval, of the basic reproduction number, and of the temporal variation of the net reproduction number of SARS-CoV-2. RESULTS: Epidemiological investigations detected over 500 cases (median age: 69, IQR: 57-78) before the first COVID-19 diagnosed patient (February 20, 2020), and suggested that SARS-CoV-2 was already circulating in at least 222 out of 1506 (14.7%) municipalities with sustained transmission across all the Lombardy provinces. We estimated the mean serial interval to be 6.6 days (95% CrI, 0.7-19). Our estimates of the basic reproduction number range from 2.6 in Pavia (95% CI, 2.1-3.2) to 3.3 in Milan (95% CI, 2.9-3.8). A decreasing trend in the net reproduction number was observed following the detection of the first case. CONCLUSIONS: At the time of first case notification, COVID-19 was already widespread in the entire Lombardy region. This may explain the large number of critical cases experienced by this region in a very short timeframe. The slight decrease of the reproduction number observed in the early days after February 20, 2020 might be due to increased population awareness and early interventions implemented before the regional lockdown imposed on March 8, 2020.


Subject(s)
COVID-19 , Aged , Communicable Disease Control , Humans , Italy/epidemiology , Retrospective Studies , SARS-CoV-2
5.
Prev Med ; 151: 106585, 2021 10.
Article in English | MEDLINE | ID: covidwho-1294322

ABSTRACT

The COVID-19 pandemic affects mortality and morbidity, with disruptions expected to continue for some time, with access to timely cancer-related services a concern. For breast cancer, early detection and treatment is key to improved survival and longer-term quality of life. Health services generally have been strained and in many settings with population breast mammography screening, efforts to diagnose and treat breast cancers earlier have been paused or have had reduced capacity. The resulting delays to diagnosis and treatment may lead to more intensive treatment requirements and, potentially, increased mortality. Modelled evaluations can support responses to the pandemic by estimating short- and long-term outcomes for various scenarios. Multiple calibrated and validated models exist for breast cancer screening, and some have been applied in 2020 to estimate the impact of breast screening disruptions and compare options for recovery, in a range of international settings. On behalf of the Covid and Cancer Modelling Consortium (CCGMC) Working Group 2 (Breast Cancer), we summarize and provide examples of such in a range of settings internationally, and propose priorities for future modelling exercises. International expert collaborations from the CCGMC Working Group 2 (Breast Cancer) will conduct analyses and modelling studies needed to inform key stakeholders recovery efforts in order to mitigate the impact of the pandemic on early diagnosis and treatment of breast cancer.


Subject(s)
Breast Neoplasms , COVID-19 , Breast Neoplasms/diagnosis , Breast Neoplasms/epidemiology , Early Detection of Cancer , Female , Humans , Mass Screening , Pandemics , Quality of Life , SARS-CoV-2
6.
Math Biosci Eng ; 18(4): 3384-3403, 2021 04 15.
Article in English | MEDLINE | ID: covidwho-1206380

ABSTRACT

Lockdown and social distancing, as well as testing and contact tracing, are the main measures assumed by the governments to control and limit the spread of COVID-19 infection. In reason of that, special attention was recently paid by the scientific community to the mathematical modeling of infection spreading by including in classical models the effects of the distribution of contacts between individuals. Among other approaches, the coupling of the classical SIR model with a statistical study of the distribution of social contacts among the population, led some of the present authors to build a Social SIR model, able to accurately follow the effect of the decrease in contacts resulting from the lockdown measures adopted in various European countries in the first phase of the epidemic. The Social SIR has been recently tested and improved through a fruitful collaboration with the Health Protection Agency (ATS) of the province of Pavia (Italy), that made it possible to have at disposal all the relevant data relative to the spreading of COVID-19 infection in the province (half a million of people), starting from February 2020. The statistical analysis of the data was relevant to fit at best the parameters of the mathematical model, and to make short-term predictions of the spreading evolution in order to optimize the response of the local health system.


Subject(s)
COVID-19 , Epidemics , Communicable Disease Control , Europe , Humans , Italy , Models, Theoretical , SARS-CoV-2
7.
Epidemiol Prev ; 44(5-6 Suppl 2): 51-59, 2020.
Article in Italian | MEDLINE | ID: covidwho-1068124

ABSTRACT

BACKGROUND: the Covid-19 pandemic has provoked a huge of clinical and epidemiological research initiatives, especially in the most involved countries. However, this very large effort was characterized by several methodological weaknesses, both in the field of discovering effective treatments (with too many small and uncontrolled trials) and in the field of identifying preventable risks and prognostic factors (with too few large, representative and well-designed cohorts or case-control studies). OBJECTIVES: in response to the fragmented and uncoordinated research production on Covid-19, the   italian Association of Epidemiology (AIE) stimulated the formation of a working group (WG) with the aims of identifying the most important gaps in knowledge and to propose a structured research agenda of clinical and epidemiological studies considered at high priority on Covid-19, including recommendations on the preferable methodology. METHODS: the WG was composed by 25 subjects, mainly epidemiologists, statisticians, and other experts in specific fields, who have voluntarily agreed to the proposal. The agreement on a list of main research questions and on the structure of the specific documents to be produced were defined through few meetings and cycles of document exchanges. RESULTS: twelve main research questions on Covid-19 were identified, covering aetiology, prognosis, interventions, follow-up and impact on general and specific populations (children, pregnant women). For each of them, a two-page form was developed, structured in: background, main topics, methods (with recommendations on preferred study design and warnings for bias prevention) and an essential bibliography. CONCLUSIONS: this research agenda represents an initial contribution to direct clinical and epidemiological research efforts on high priority topics with a focus on methodological aspects. Further development and refinements of this agenda by Public Health Authorities are encouraged.


Subject(s)
COVID-19/epidemiology , Epidemiologic Research Design , Pandemics , Research , SARS-CoV-2 , Adult , Aged , COVID-19/drug therapy , COVID-19/therapy , Child , Epidemiology/organization & administration , Female , Humans , Italy/epidemiology , Male , Middle Aged , Pregnancy , Pregnancy Complications, Infectious/epidemiology , Prognosis , Societies, Scientific , Therapeutic Equipoise
8.
Epidemiol Prev ; 44(5-6 Suppl 2): 42-50, 2020.
Article in Italian | MEDLINE | ID: covidwho-1068123

ABSTRACT

The article compares two of the most followed indices in the monitoring of COVID-19 epidemic cases: the Rt and the RDt indices. The first was disseminated by the Italian National Institute of Health (ISS) and the second, which is more usable due to the lower difficulty of calculation and the availability of data, was adopted by various regional and local institutions.The rationale for the Rt index refers to that for the R0 index, the basic reproduction number, which is used by infectivologists as a measure of contagiousness of a given infectious agent in a completely susceptible population. The RDt index, on the other hand, is borrowed from the techniques of time series analysis for the trend of an event measurement that develops as a function of time. The RDt index does not take into account the time of infection, but the date of the diagnosis of positivity and for this reason it is defined as diagnostic replication index, as it aims to describe the intensity of the development of frequency for cases recognized as positive in the population.The comparison between different possible applications of the methods and the use of different types of monitoring data was limited to four areas for which complete individual data were available in March and April 2020. The main problems in the use of Rt, which is based on the date of symptoms onset, arise from the lack of completeness of this information due both to the difficulty in the recording and to the absence in asymptomatic subjects.The general trend of RDt, at least at an intermediate lag of 6 or 7 days, is very similar to that of Rt, as confirmed by the very high value of the correlation index between the two indices. The maximum correlation between Rt and RDt is reached at lag 7 with a value of R exceeding 0.97 (R2=0.944).The two indices, albeit formally distinct, are both valid; they show specific aspects of the phenomenon, but provide basically similar information to the public health decision-maker. Their distinction lies not so much in the method of calculation, rather in the use of different information, i.e., the beginning of symptoms and the swabs outcome.Therefore, it is not appropriate to make a judgment of preference for one of the two indices, but only to invite people to understand their different potentials so that they can choose the one they consider the most appropriate for the purpose they want to use it for.


Subject(s)
Basic Reproduction Number , COVID-19/epidemiology , Epidemiological Monitoring , Pandemics , SARS-CoV-2/pathogenicity , Decision Making , Health Policy , Humans , Incidence , Italy/epidemiology , Nasopharynx/virology , Risk , SARS-CoV-2/isolation & purification , Symptom Assessment , Time Factors
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