cord-004041-2b2h1xog	2019	
cord-004110-xc8vv9x8	2020	
cord-005279-w69ao8ic	2013	
cord-005508-6zlqny9m	2020	
cord-032716-i6hfj8ca	2020	
cord-103711-tnw82hbm	2020	
cord-248932-i1v2lyd2	2020	
cord-255560-c8s9f12f	2020	
cord-257099-8k28vkgf	2020	
cord-263518-6puccigu	2020	
cord-265682-yac7kzaf	2020	
cord-269679-dfma5kqc	2020	key: cord-269679-dfma5kqc authors: Badshah, Syed Lal; Ullah, Asad; Badshah, Syed Hilal; Ahmad, Irshad cord_uid: dfma5kqc Iran was initially reluctant to close its borders with its neighbors as religious tourism is a big part of its revenue generation and the international community has already imposed economic sanctions over it due to its nuclear program. 3 Every year approximately 0.7 million Shia sect Muslims from Pakistan visit for a pilgrimage to various shrines in the cities of Iran that include Qom, Tehran, Tabriz, and Mashhad. It has been estimated that there are over eight thousand sacred sites in Iran alone and every year around eight million foreigners visit these shrines ( Figure 1 ). The pilgrimage mostly includes visits to cities like Karbala, Najaf, Kufa, Samara, and Baghdad in Iraq and several places in Damascus in Syria. Estimation of Coronavirus Disease 2019 (COVID-19) Burden and Potential for International Dissemination of Infection From Iran COVID-19 battle during the toughest sanctions against Iran The authors declared no conflict of interest.
cord-269818-ko14wjf7	2020	
cord-270614-4q7itegc	2020	We argue that reflexive comparative analysis bridging social and visual analysis, anchored in embodied conditions of such people, offers a way to learn from responses to COVID-19 while also being an exercise in ethical research practice. We argue that reflexive comparative analysis bridging social and visual analysis, anchored in embodied conditions of such people, offers a way to learn from responses to COVID-19 while also being an exercise in ethical research practice. Such rituals have been repeated for millennia, and there are local and regional variations in the way people in Iran and its bordering countries and their diasporas enact Nowruz and the haft seen. This is a new Fig. 1 Separate, but together: Changing haft seen and Nowruz practices to care for each other within conditions imposed by COVID-19 experience for us, who have shared a roof for more than a decade.
cord-271679-94h6rcih	2020	
cord-272828-13i2y9kc	2020	
cord-276583-j8bf0eme	2012	
cord-283133-jspfwuqu	2020	
cord-294690-fpjhkb4g	2020	
cord-301720-majpfxqn	2017	
cord-303331-xolksoy3	2020	
cord-306925-yt5cscf1	2018	
cord-309762-p266f3el	2020	
cord-311495-svgw59ic	2020	
cord-312784-ykko0al5	2020	
cord-313286-nqvuas3p	2020	
cord-313904-745u0si8	2020	
cord-315925-hnvf634e	2020	
cord-318043-1x3dp1vv	2020	
cord-320895-y6pzrbdi	2020	
cord-322796-ojfrvtuy	2020	
cord-328930-5a0z1ryz	2020	
cord-331701-izkz1hz4	2020	
cord-336192-5uxq5xrs	2020	
cord-337000-k1qq4qgg	2020	
cord-339235-8xslz4bs	2018	
cord-340132-t77pab71	2020	
cord-342517-bzmhjvr5	2020	
cord-347353-ll2pnl81	2020	
cord-348111-fkjmzpuw	2020	title: A spatio-temporal geodatabase of mortalities due to respiratory tract diseases in Tehran, Iran between 2008 and 2018: a data note Mortality rates due to respiratory tract diseases (MRRTDs) follow a spatial pattern and this may suggest a potential link between environmental risk factors and MRRTDs. Spatial analysis of RTDs mortality data in an urban setting can provide new knowledge on spatial variation of potential risk factors for RTDs. This will enable health professionals and urban planners to design tailored interventions. Spatio-temporal analyses of mortality data can provide new knowledge on spatial variation of MRRTDs and potential Open Access BMC Research Notes *Correspondence: kiani.behzad@gmail.com drivers of this variation. Data on 43,176 death events due to RTDs from September 2008 to September 2018 were obtained from the Behesht-e Zahra Organization, a local health department under the supervision of the Tehran Municipality [15] . Data for: mortality due to respiratory tract diseases in Tehran Iran between
cord-351941-fgtatt40	2020	Estimates using data up to March 20th, 2020, point to 916,000 (90% UI: 508 K, 1.5 M) cumulative cases and 15,485 (90% UI: 8.4 K, 25.8 K) total deaths, numbers an order of magnitude higher than official statistics. The current paper focuses on using a standard dynamic epidemiological model as a tool for incorporating various sources of data into a unified estimation of the actual trajectory of disease, applying the method to COVID-19 outbreak in Iran. We also use unofficial data points including four observations about the number of Iranian passengers diagnosed with COVID-19 upon arrival in international airports, and three estimates aggregated by healthcare providers in Iran and reported by BBC and Iran International news agencies about total cases of death from COVID-19. We define a likelihood function for change over time (net-inflow) of official reports on cumulative death, recovered and infection assuming they are count events drawn from model-predicted rates (Poisson distribution).
cord-353976-gns5omyb	2020	
cord-356117-ksfcc8x8	2020