Collaborative　decision-making　across　multiple　government　agencies　is　considered　a　critical　and　effective　strategy　to　combat　public　health　crisis;　however,　we　know　little　about　how　the　collaborative　decision-making　works　and　evolves　during　periods　of　crisis.　To　fill　this　lacuna,　this　study　uncovers　the　structure　and　evolving　dynamics　of　the　network　by　employing　a　policy　document　analysis.　Based　on　the　policy　documents,　jointly　issued　by　the　agencies　of　Chinese　central　government　in　four　phases　regarding　COVID-19　control,　we　first　constructed　a　co-occurrence　matrix　of　policy-issuing　agencies　to　outline　the　network　structure,　then　drew　a　breadth-depth　matrix　to　identify　the　role　evolution　of　agencies,　and　lastly　built　a　two-mode　network　consisting　of　policy　topics　and　agencies　to　determine　the　evolution　mechanisms　of　policy　attentions　for　each　agency.　It　was　found　that　the　network　structure　of　interagency　collaboration　involves　three　forms:　discrete　structure　in　the　early　phase,　subgroup　structure　in　the　middle　phase,　and　connected　structure　in　the　latter　phase.　Agencies　embedded　in　the　network　can　be　categorized　into　three　types:　leading　agencies,　key　agencies,　and　auxiliary　agencies,　with　their　constituent　members　changed　as　the　pandemic　risks　are　gradually　becoming　under　control.　Furthermore,　each　type　has　its　own　primary　policy　attentions,　but　shares　some　common　foci　in　all　four　phases　and　shifts　attention　in　the　emergency　management　process.　This　study　contributes　to　shedding　light　on　the　formation　of　and　variations　in　collaborative　networks　in　health　emergencies　and　provides　policy　implications　for　other　countries　that　have　struggled　against　COVID-19.