The study was aimed at determining whether it is financially beneficial to public transport owners of vehicles in urban setting to wait for passengers at rush hours for a long time at the bus stop until the bus is full while a crowd of people is waiting for the same bus at the end of the other bus stop.The study was carried in using a mathematical model of transport lines to which is adjusted the phenomenon of lines of buses at the bus terminus where people who want to go to the other end of the line come in small numbers to take place in the lined up vehicles. This model of traffic regulation of public transport has been financially compared to the model where the buses do not queue up at the bus terminus. The decision has been taken in comparing the fare to be paid by passengers to the variable cost of exploitation attributable to each of them.Out of the four lines of transport selected for the study in Lubumbashi city in the Democratic Republic of Congo, namely the lines Town-CRAA, Town-Ruashi, Town-Kisanga and Town-Kisima, the last three lines are in conformity with the mathematical model of reference. The current single fare of 500 Congolese Francs being higher than the variable costs of exploitation on these three lines of transport, that is to say, respectively 175, 150 and 145 Congolese Francs, then the model of traffic regulation without buses queuing at the bus terminus of the city Centre is more cost-effective.

The aim of this study was to assess the capacity of the Katuba district hospital to address felt needs for hospitalization of patients. To do it, information on the activity of hospitalization contained in the registers of patients and the reports of the district medical officer were collected and used to determine indicators related to the hospitalization. The queuing model was used to determine the daily characteristics of the hospitalization. As results, the initial bed occupancy rates in different inpatient services were 162 % in the pediatrics ward, 98 % in the maternity, 97 % in the surgery ward, 43 % in the male internal medicine ward and 43 % in the female internal medicine ward. According to needs of hospitalization, redistribution of beds was proposed and returned the above bed occupancy rates respectively to 94 %, 94 %, 87 %, 91 % and 85 %. The queuing model applied on each inpatient service revealed that the daily average numbers of patients awaiting an available bed are respectively of 9, 11, 4, 8, and 4, with a waiting time respectively estimated at 2,26 ; 2,69 ; 6,1 ; 8,16 and 5,48 days. Definitely, disparities of the initial bed occupancy rates highlight an inefficient distribution of beds between inpatient services, and the fact that patients wait for days before being admitted to hospital indicates that the capacity of the hospital is insufficient and should be improved.